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Videos uploaded by user “MarinStatsLectures-R Programming & Statistics”
What is RStudio and Why Should You Download It? |R Tutorial 1.1| MarinStatsLectures
 
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What is RStudio and why you should download it. For more Statistics and R Programming Tutorials: https://goo.gl/4vDQzT RStudio is a free, open source, user interface for R programming language, that makes working with R much easier. R Studio adds functionality to R, includes many menu options, and other ways to keep your work neat and organized. here is a quick overview of the topics covered i n this video: 00:00:16 What is RStudio 00:00:24 What does RStudio do? 00:00:45 How to create vectors and plots in R programming language using R console? 00:01:09 How to use the LS command to see objects in R’s memory? 00:01:29 a quick look at RStudio 00:01:36 How to create vectors and plots in Rstudio 00:01:59 How to save a plot in R using RStudio 00:02:23 How to Import data into R using RStudio 00:03:03 How to sort the data imported in R using RStudio 00:03:16 How to create and manage scripts within RStudio? 00:03:22 How to create and submit new commands in RStudio? 00:03:35 How to add up numbers in R programming language using RStudio? 00:03:53 How to save the scripts of code in R programming language,using RStudio? 00:04:18 What is R Markdown? 00:04:30 How to create new projects in R programming language using RStudio? This video is a tutorial for programming in R Statistical Software for beginners, using RStudio. ♠︎♣︎♥︎♦︎To learn more: Subscribe: https://goo.gl/4vDQzT website: http://statslectures.com Facebook:https://goo.gl/qYQavS Twitter:https://goo.gl/393AQG Instagram: https://goo.gl/fdPiDn Our Team: Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at UBC. Producer: Ladan Hamadani (B.Sc., BA., MPH) These #RTutorial are created by #marinstatslectures to support the statistics course (#SPPH400) at The University of British Columbia(UBC) although we make all videos available to the public for free.
Multiple Linear Regression in R (R Tutorial 5.3)
 
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Learn how to fit and interpret output from a multiple linear regression model in R and produce summaries. You will learn to use "lm", "summary", "cor", "confint" commands. You will also learn the "plot" command for producing residual and QQ plots. It will be helpful to first review our video on simple linear regression. The video provides a tutorial for programming in R Statistical Software for beginners. You can access and download the "LungCapData" dataset here: Excel format: https://bit.ly/LungCapDataxls Tab Delimited Text File: https://bit.ly/LungCapData Here is a quick overview of the topic addressed in this video: 0:00:07 why use Multiple Linear Regression Model 0:00:32 using the "lm" command to fit a linear model 0:00:36 how to access the help menu in R for multiple linear regression by typing "help" 0:01:06 fitting a linear regression model using Age and Height as the explanatory or X variables 0:01:19 producing and interpreting the summary of linear regression model fit in R 0:03:16 how to calculate Pearson's correlation between the two variables 0:03:26 how to interpret the collinearity between two variables 0:03:49 how to create a confidence interval for the model coefficients using the "confint" command 0:03:57 interpreting the confidence interval for our model's coefficients 0:04:13 fitting a linear model using all of the X variables 0:04:27 how to check the model assumptions by examining plots of the residuals or errors using the "plot(model)" command
Simple Linear Regression in R | R Tutorial 5.1| MarinStatsLectures
 
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Simple Linear Regression in R ; For more Statistics and R Programming Tutorials: https://goo.gl/4vDQzT; Simple Linear Regression Concept and Terminology: https://goo.gl/VhWmVD ;Dataset: https://goo.gl/tJj5XG How to fit a Linear Regression Model in R, Produce Summaries and ANOVA table for it. ◼︎ What to Expect in this R Tutorial: ►In this R video tutorial you will learn When to use a regression model, and how to use the “lm” command in R to fit a linear regression model for your data ► Here you will also learn to produce summaries for your regression model using “summary” command in R statistics software; these summaries can include intercept, test statistic, p value, and estimates of the slope for your linear regression model ► in this tutorial, you will also become familiar with the Residual Error: a measure of the variation of observations in regression line ► You will also learn to ask R programming software for the attributes of the simple linear regression model using "attributes" command, extract certain attributes from the regression model using the dollar sign ($), add a regression line to a plot in R using "abline" command and change the color or width of the regression line. ► this R tutorial will show you how to get the simple linear regression model's coefficient using the "coef" command or produce confidence intervals for the regression model using "confint" commands; moreover, you will learn to change the level of confidence using the "level" argument within the "confint" command. ►You will also learn to produce the ANOVA table for the linear regression model using the "anova" command, explore the relationship between ANOVA table and the f-test of the regression summary, and explore the relationship between the residual standard error of the linear regression summary and the square root of the mean squared error or mean squared residual from the ANOVA table. ► ►You can access and download the dataset here: https://statslectures.com/r-stats-datasets ► ► Watch this Statistics Tutorial on the concept and terminology for Simple Linear Regression Model https://youtu.be/vblX9JVpHE8 ◼︎ Table of Content: 0:00:07 When to fit a simple linear regression model? 0:01:11 How to fit a linear regression model in R using the "lm" command 0:01:14 How to access the help menu in R for any command 0:01:36 How to let R know which variable is X and which one is Y when fitting a regression model 0:01:45 How to ask for the summary of the simple linear regression model in R including estimates for intercept, test statistic, p-values and estimates of the slope. 0:02:27 Residual standard error (residual error) in R 0:02:53 How to ask for the attributes of the simple linear regression model in R 0:03:06 How to extract certain attributes from the simple linear regression model in R 0:03:40 How to add a regression line to a plot in R 0:03:52 How to change the color or width of the regression line in R 0:04:07 How to get the simple linear regression model's coefficient in R 0:04:11 How to produce confidence intervals for model's coefficients in R 0:04:21 How to change the level of confidence for model's coefficients in R 0:04:38 How to produce the ANOVA table for the linear regression in R 0:04:47 Explore the relationship between ANOVA table and the f-test of the linear regression summary 0:04:55 Explore the relationship between the residual standard error of the linear regression summary and the square root of the mean squared error or mean squared residual from the ANOVA table ♠︎♣︎♥︎♦︎To learn more: Subscribe: https://goo.gl/4vDQzT website: http://statslectures.com Facebook:https://goo.gl/qYQavS Twitter:https://goo.gl/393AQG Instagram: https://goo.gl/fdPiDn Our Team: Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at UBC. Producer: Ladan Hamadani (B.Sc., BA., MPH) These #RTutorial are created by #marinstatslectures to support the statistics course (#SPPH400) at The University of British Columbia(UBC) although we make all videos available to the public for free.
Import Data, Copy Data from Excel to R CSV & TXT Files | R Tutorial 1.5 |MarinStatsLectures
 
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Import Data, Copy Data from Excel (or other spreadsheets) to R CSV & TXT Files; Practice with Dataset: https://goo.gl/tJj5XG More Statistics and R Programming Tutorials: https://goo.gl/4vDQzT How to Import CSV data into R or How to Import TXT files into R from Excel or other spreadsheets using function in R ▶︎How to import CSV data into R? We will be using "read.table" function to import comma separated data into R ▶︎ How to import txt data file into R? You will learn to use "read.delim" function to import the data to R ▶︎ In addition, you will also learn to use "file.choose" argument for file location, "header" argument to let R know the data has headers or variable names and "sep" argument to let R know how the data values are separated. ▶︎▶︎Download the dataset here: https://statslectures.com/r-stats-datasets ▶︎▶︎Watch More: ▶︎Intro to Statistics Course: https://bit.ly/2SQOxDH ▶︎Getting Started with R: https://bit.ly/2PkTneg ▶︎Graphs and Descriptive Statistics in R: https://bit.ly/2PkTneg ▶︎Probability distributions in R: https://bit.ly/2AT3wpI ▶︎Bivariate analysis in R: https://bit.ly/2SXvcRi ▶︎Linear Regression in R: https://bit.ly/1iytAtm ◼︎ Table of Content 0:00:17 What are the two main file types for saving a data file 0:00:36 How to save an Excel file as a CSV file (comma-separated value) 0:01:10 How to open a CSV data file in Excel 0:01:20 How to open a CSV file in text editor 0:01:36 How to import CSV file into R? using read.csv function 0:01:44 How to access the help menu for different commands/functions in R 0:02:04 How to specify file location in R? using file.choose argument on read.csv function 0:02:31 How to let R know data has headers or variable names? using the header argument on read.csv function 0:03:22 How to import CSV file into R? using read.table function 0:03:38 How to specify the file location in R for read.table function? using file.choose argument 0:03:46 How to specify in R know how the data values are separated? the "sep" argument on read.table function 0:04:10 How to save a file in Excel as tab-delimited text (TXT) file 0:04:50 How to open a tab-delimited (.TXT) data file in a text editor 0:05:07 How to open a tab-delimited (.TXT) data file in excel 0:05:20 How to import tab-delimited (.TXT) data file into R? using read.delim function 0:05:44 How to to specify the file path for read.delim function in R? using file.choose argument 0:06:06 How to import tab-delimited (.TXT) data file into R? using read.table function 0:06:23 How to specify that the data has headers or variable in R?Using header argument on read.table function This video is a tutorial for programming in R Statistical Software for beginners, using RStudio. Follow MarinStatsLectures Subscribe: https://goo.gl/4vDQzT website: https://statslectures.com Facebook:https://goo.gl/qYQavS Twitter:https://goo.gl/393AQG Instagram: https://goo.gl/fdPiDn Our Team: Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at UBC. Producer and Creative Manager: Ladan Hamadani (B.Sc., BA., MPH) The #RTutorial is created by #marinstatslectures to support the statistics course (SPPH400 #IntroductoryStatistics) at The University of British Columbia(UBC) although we make all videos available to the everyone everywhere for free! Thanks for watching! Have fun and remember that statistics is almost as beautiful as a unicorn!
Subsetting (Sort/Select) Data in R with Square Brackets | R Tutorial 1.9| MarinStatsLectures
 
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Subsetting (Sort/Select) Data with Square Brackets and Logic Statements in R; Practice with LungCap Dataset: https://goo.gl/tJj5XG; More Statistics and R Programming Tutorials: https://goo.gl/4vDQzT When working with a large data set, you might only be interested in a small portion of it. How do you sort through all the variables and observations and extract only the data that you need? R has several ways of sorting and selecting data in a process that is called “subsetting.” Brackets in R lets you select, or subset, data from a vector, matrix, array, list or data frame. R’s operators can be summarized as: • [ for subsets, • [[ for extracting items, and • $ for extracting by name. In this video, we focus on subsetting data from a vector and matrix in R. ▶︎▶︎Download the LungCap dataset here: https://statslectures.com/r-stats-datasets ▶︎▶︎Watch More: ▶︎Starting with R, Tutorials https://bit.ly/2zaFd5b ▶︎Graphs and Descriptive Statistics in R: https://bit.ly/2PkTneg ▶︎Probability Distributions in R: https://bit.ly/2AT3wpI ▶︎Bivariate Analysis in R: https://bit.ly/2SXvcRi ▶︎Linear Regression in R: https://bit.ly/1iytAtm ▶︎Intro to Statistics Course: https://bit.ly/2SQOxDH ◼︎ Table of Content 0:00:19 How to ask R programming language the dimensions of the data? using the "dim" or dimensions function 0:00:31 How to ask R about the number of observations in a vector or variable? using the "length" function 0:00:41 How to use square brackets to extract part of the data from a vector in R 0:01:10 How to extract (subset) data from a matrix or data frame in R (step by step examples) 0:01:36 the difference between "equal sign" (=) and "double equal sign" (==) in R Software 0:03:25 how to pull out a subset of data from a dataset in R: step by step example This video is a tutorial for programming in R Statistical Software for beginners. Follow MarinStatsLectures Subscribe: https://goo.gl/4vDQzT website: https://statslectures.com Facebook:https://goo.gl/qYQavS Twitter:https://goo.gl/393AQG Instagram: https://goo.gl/fdPiDn Our Team: Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at UBC. Producer and Creative Manager: Ladan Hamadani (B.Sc., BA., MPH) These videos are created by #marinstatslectures to support a course at The University of British Columbia (UBC) (SPPH400: #IntroductoryStatistics and #RTutorial for Health Science Research), although we make all videos available to the public for free. Thanks for watching! Have fun and remember that statistics is almost as beautiful as a unicorn!
ANOVA, Multiple Comparisons & Kurskal Wallis in R | R Tutorial 4.6 | MarinStatsLectures
 
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Analysis Of Variance (ANOVA), Multiple Comparisons & Kurskal Wallis in R ; Dataset: https://bit.ly/2RNeR0f ANOVA Explanation: https://goo.gl/QfQv9b More Statistics and R Programming Tutorials: https://goo.gl/4vDQzT How to conduct one way Analysis of Variance (ANOVA) in R, ANOVA Pairwise Comparison in R, (Multiple Comparisons in R), and Kruskal Wallis one-way ANOVA in R: ►►In this Tutorial you will learn to use various commands to : ► Conduct one way analysis of variance ANOVA test in R ►View ANOVA table in R ►Produce a visual display for the pair-wise comparisons of the analysis of variance in R ► Conduct multiple comparisons/ANOVA pair-wise comparisons in R ► Produce Kruskal-Wallis one-way analysis of variance using ranks with R Statistical Software. ▶︎To access and download the dataset visit https://www.statslectures.com/ ■Table of Content 0:00:12 when to use one-way analysis of variance (ANOVA) 0:00:37 how to conduct ANOVA in R using the "aov" command 0:00:42 how to access the help menu in R for ANOVA commands 0:00:52 how to create a boxplot in R 0:01:42 how to view ANOVA table in R using "summary" command 0:02:07 how to ask R to let us know what is stored in an object using the "attributes" command. 0:02:23 how to extract certain attributes from an object in R using the dollar sign ($) 0:02:48 how to conduct multiple comparisons/pair-wise comparisons for the analysis of variance in R using the "TukeyHSD" command 0:03:17 how to produce a visual display for the pair-wise comparisons of the analysis of variance in R using "plot" command 0:03:50 how to produce Kruskal-Wallis one-way analysis of variance using ranks in R using the "kruskal.test" command 0:03:56 when is it appropriate to use Kruskal-Wallis one-way analysis of variance for data This video is a tutorial for programming in R Statistical Software for beginners, using RStudio. ▶︎▶︎ Watch More ▶︎ANOVA Use and Assumptions https://youtu.be/_VFLX7xJuqk ▶︎ Understanding Sum of Squares in ANOVA ,concept of analysis of variance, and ANOVA hypothesis testing https://youtu.be/-AeU4y2vkIs ▶︎ ANOVA Test Statistic and P Value: https://youtu.be/k-xZzEYL8oc ▶︎ ANOVA & Bonferroni Multiple Comparisons Correction https://youtu.be/pscJPuCwUG0 ▶︎ Two Sample t test for independent groups https://youtu.be/mBiVCrW2vSU ▶︎ Paired t test https://youtu.be/Q0V7WpzICI8 Follow MarinStatsLectures Subscribe: https://goo.gl/4vDQzT website: https://statslectures.com Facebook:https://goo.gl/qYQavS Twitter:https://goo.gl/393AQG Instagram: https://goo.gl/fdPiDn Our Team: Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at UBC. Producer: Ladan Hamadani (B.Sc., BA., MPH) These #RTutorial are created by #marinstatslectures to support the statistics course (#SPPH400) at The University of British Columbia(UBC) although we make all videos available to the public for free. Thanks for watching! Have fun and remember that statistics is almost as beautiful as a unicorn!
Mann Whitney U aka Wilcoxon Rank-Sum Test in R (R Tutorial 4.3)
 
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Learn how to conduct the Wilcoxon Rank-Sum (aka Mann-Whitney U) test in R. This is the non-parametric alternative to the independent t-test. We will discuss the "wilcox.test", "exact" and "correct" commands in R. This video is a tutorial for programming in R Statistical Software for beginners. Download the LungCapData dataset here: Excel format: https://bit.ly/LungCapDataxls Tab Delimited Text File: https://bit.ly/LungCapData Here is a quick overview of the topics addressed in this video: 0:00:11 when is it appropriate to use the "Mann-Whitney U" AKA "Wilcoxon Rank-Sum" test to analyze data 0:00:56 how to use the "wilcox.test" command in R to conduct the nonparametric test of examining the difference in median for two independent populations 0:01:02 how to access the Help menu in R for Mann-Whitney U AKA Wilcoxon Rank-Sum test 0:01:20 how to visually examine the relationship between two independent variables using "boxplot" command before conducting "Mann-Whitney U" AKA "Wilcoxon Rank-Sum" test 0:01:42 how to conduct a two-sided nonparametric test in R using the "wilcox.test" command 0:01:59 how to let R know that the difference in medians for the independent populations is 0 using the "mu" argument 0:02:06 how to let R know to calculate a two-sided alternative using the "alt" argument 0:02:12 how to let R know to return a nonparametric confidence interval using the "conf.int" argument 00:02:21 how to set the level of confidence interval using the "conf.level" argument 0:02:29 how to specify that the groups are not paired using the "paired" argument 0:02:41 how to ask R to return an exact p-value using the "exact" argument 0:02:48 how to ask R to use a continuity correction using the "correct" argument
Binomial Distribution in R | R Tutorial 3.1| MarinStatsLectures
 
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Binomial Distribution in R; For more Statistics and R Programming Tutorials: https://goo.gl/4vDQzT -Sample vs Population (Histograms vs Probability Distributions) Statistics Tutorial: https://youtu.be/DOnucdP7LNU - Dataset: https://goo.gl/tJj5XG How to calculate probabilities for binomial random variables in R. In this R tutorial, you will learn to use the "pbinom" and "dbinom" commands to calculate probabilities for the binomial random variables. Here you will use "dbinom" command in order to have multiple probabilities returned in R and "sum" command to calculate cumulative probabilities for the binomial random variable. You will also learn to calculate cumulative probabilities in R for the binomial random variable using the "pbinom" command. This video is a tutorial for programming in R Statistical Software for beginners. Here is a quick overview of the topics addressed in this video: 0:00:10 introducing the binomial random variable used in this video and its characteristics 0:00:24 how to calculate probabilities for the binomial random variable in R using the "pbinom" or "dbinom" functions 0:00:32 how to access the help menu in R for calculating probabilities for binomial random variables 0:00:43 how to use the "dbinom" command in R to calculate probability for the binomial random variable 0:01:24 how to have multiple probabilities returned in R for the binomial random variable using the "dbinom" command 0:02:10 how to calculate cumulative probabilities in R for the binomial random variable using the "sum" command 0:02:45 how to calculate cumulative probabilities in R for the binomial random variable using the "pbinom" command 0:03:30 "rbinom" command in R 0:03:38 "qbinom" command in R ►►You can access and download the dataset here: https://statslectures.com/r-stats-datasets ♠︎♣︎♥︎♦︎To learn more: Subscribe: https://goo.gl/4vDQzT website: http://statslectures.com Facebook:https://goo.gl/qYQavS Twitter:https://goo.gl/393AQG Instagram: https://goo.gl/fdPiDn Our Team: Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at UBC. Producer: Ladan Hamadani (B.Sc., BA., MPH) These #RTutorial are created by #marinstatslectures to support the statistics course (#SPPH400) at The University of British Columbia(UBC) although we make all videos available to the public for free.
Checking Linear Regression Assumptions in R | R Tutorial 5.2 | MarinStatsLectures
 
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Checking Linear Regression Assumptions in R ; Dataset: https://goo.gl/tJj5XG; Linear Regression Concept and with R: https://bit.ly/2z8fXg1; More Statistics and R Programming Tutorials: https://goo.gl/4vDQzT; How to test linear regression assumptions in R? In this R tutorial, we will first go over some of the concepts for linear regression like how to add a regression line, how to interpret the regression line (predicted or fitted Y value, the mean of Y given X), how to interpret the residuals or errors (the difference between observed Y value and the predicted or fitted Y value) and the assumptions when fitting a linear regression model. Then we will discuss the regression diagnostic plots in R, the reason for making diagnostic plots, and how to produce these plots in R; You will learn to check the linearity assumption and constant variance (homoscedasticity) for a regression model with residual plots in R and test the assumption of normality in R with QQ (Quantile Quantile) plots. You will also learn to check the constant variance assumption for data with non-constant variance in R, produce and interpret residual plots, QQ plots, and scatterplots for data with non-constant variance, and produce and interpret residual plots, QQ plots, and scatterplots for data with non-linear relationship in R. ►► Download the dataset here: https://statslectures.com/r-stats-datasets ►► Watch More: ►Linear Regression Concept and Linear Regression with R Series: https://bit.ly/2z8fXg1 ►Simple Linear Regression Concept https://youtu.be/vblX9JVpHE8 ►Nonlinearity in Linear Regression https://youtu.be/tOzwEv0PoZk ► R Squared of Coefficient of Determination https://youtu.be/GI8ohuIGjJA ► Linear Regression in R Complete Series https://bit.ly/1iytAtm ■ Table of Content: 0:00:29 Introducing the data used in this video 0:00:49 How to fit a Linear Regression Model in R? 0:01:03 how to produce the summary of the linear regression model in R? 0:01:15 How to add a regression line to the plot in R? 0:01:24 How to interpret the regression line? 0:01:43 How to interpret the residuals or errors? 0:01:53 where to find the Residual Standard Error (Standard Deviation of Residuals) in R 0:02:14 What are the assumptions when fitting a linear regression model and how to check these assumptions 0:03:01 What are the built-in regression diagnostic plots in R and how to produce them 0:03:24 How to use Residual Plot for testing linear regression assumptions in R 0:03:50 How to use QQ-Plot in R to test linear regression assumptions 0:04:33 How to produce multiple plots on one screen in R 0:05:00 How to check constant variance assumption for data with non-constant variance in R 0:05:12 How to produce and interpret a Scatterplot and regression line for data with non-constant variance 0:05:40 How to produce and interpret the Residual plot for data with non-constant variance in R 0:06:02 How to produce and interpret the QQ plot for data with non-constant variance in R 0:06:12 How to produce and interpret a Scatterplot with regression line for data with non-linear relationship in R 0:06:40 How to produce and interpret the Residual plot for a data with non-linear relationship in R 0:06:52 How to produce and interpret the QQ plot for a data with non-linear relationship in R 0:07:02 what is the reason for making diagnostic plots Follow MarinStatsLectures Subscribe: https://goo.gl/4vDQzT website: https://statslectures.com Facebook:https://goo.gl/qYQavS Twitter:https://goo.gl/393AQG Instagram: https://goo.gl/fdPiDn Our Team: Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at UBC. Producer and Creative Manager: Ladan Hamadani (B.Sc., BA., MPH) These #RTutorials are created by #marinstatslectures to support a course at The University of British Columbia (#UBC) although we make all videos available to the everyone everywhere for free. Thanks for watching! Have fun and remember that statistics is almost as beautiful as a unicorn!
Download, Install and Setup R & RStudio | R Tutorial 1.2 | MarinStatsLectures
 
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Download and install R Statistical Software and RStudio. For more Statistics and R Programming Tutorials: https://goo.gl/4vDQzT To download R programming Software go to https://www.r-project.org and to download R Studio go to https://www.rstudio.com ◼︎ Topics addressed in this video: 0:00:27 how to download R from https://www.r-project.org 0:00:41 how to download R through one of the CRAN pages 0:00:53 how to select a mirror (location) to download R from. 0:01:40 how to install R programming language on your computer: step by step 0:02:37 how to download and install RStudio 0:02:43 download RStudio from https://www.rstudio.com 0:03:37 how to install RStudio on your computer: step by step This video is a tutorial for programming in R Statistical Software for beginners, using R Studio. ♠︎♣︎♥︎♦︎To learn more: Subscribe: https://goo.gl/4vDQzT website: http://statslectures.com Facebook:https://goo.gl/qYQavS Twitter:https://goo.gl/393AQG Instagram: https://goo.gl/fdPiDn Our Team: Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at UBC. Producer: Ladan Hamadani (B.Sc., BA., MPH) These #RTutorial are created by #marinstatslectures to support the statistics course (#SPPH400) at The University of British Columbia(UBC) although we make all videos available to the public for free.
Chi-Square Test, Fishers Exact Test, and Cross Tabulations in R (R Tutorial 4.7)
 
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Learn how to conduct the Chi-square test of independence and Fisher's Exact test, as well as produce cross tabulations. You will learn the "chisq.test", "fisher.test", "barplot", "correct", "attributes" and "table" commands. This video is a tutorial for programming in R Statistical Software for beginners. Download the LungCapData dataset here: Excel format: https://bit.ly/LungCapDataxls Tab Delimited Text File: https://bit.ly/LungCapData Here is a quick overview of the topics addressed in this video 0:00:10 when is it appropriate to use the chi-square test of independence to analyzee the data 0:00:35 how to use the "chisq.test" command in R 0:00:42 how to access the Help menu in R for the chi-square test of independence 0:00:53 how to produce a contingency table for two categorical variables in R using the "table" command 0:01:15 how to visually examine the relationship between two categorical variables before conducting the chi-square test of independence 0:01:26 how to produce clustered bar charts using "besides" argument 0:01:42 how to use the "chisq.test" command in R to produce the chi-square test for the contingency table 0:01:54 how to use the "correct" argument in R to do the Yate's continuity correction for the chi-square test 0:02:30 how to ask R to return attributes stored in an object using "attributes" command 0:02:42 how to extract certain attributes from an object in R using the "$" 0:03:00 when is it appropriate to use Fisher's exact test 0:03:07 how to use the "fisher.test" command in R to do Fisher's exact test 0:03:16 how to ask R to return confidence interval for the odds ratio using the "conf.int" argument 0:03:24 how to set the desired level of confidence using the "conf.level" argument
Histograms in R | R Tutorial 2.3 | MarinStatsLectures
 
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Histograms in R; For more Statistics and R Programming Tutorials: https://goo.gl/4vDQzT - Sample vs Population (Histograms vs Probability Distributions) Statistics Tutorial: https://youtu.be/DOnucdP7LNU - Dataset: https://goo.gl/tJj5XG ►How to produce histograms in R and add a density curve to the plot using the "hist" and "lines" commands. This tutorial will explain how to modify the histogram by adding titles, changing axes labels, changing the line colour or width and many more by using "main", "xlab", "xlim", "col", "lwd" arguments and more . This video tutorial provides an interaction for beginners to programming in R Statistical Software. ►►You can access and download the dataset here: https://statslectures.com/r-stats-datasets ►here is a quick look at the topics addressed in this video; use the timestamps to jump to any topic in the video 0:00:05 What is a histogram and is it appropriate to use a histogram for your data 0:00:25 how to produce a histogram in R using the "hist" command 0:00:30 how to access the help menu for histogram in R 0:00:42 What are the default options for histogram plots in R "Modifying a histogram in R": 0:01:03 how to change the y-axis of a histogram to represent a "probability density" rather than "frequencies" using "freq" argument or "prob" argument 0:01:45 how to change the x or y limits of a histogram in R using the "xlim" or "ylim" argument 0:02:01 how to change the "bin width" of a histogram using the "breaks" argument 0:03:08 how to add a title to a histogram in R using the "main" argument 0:03:18 how to add labels to the x-axis or y-axis of a histogram in R using "xlab" or "ylab" arguments 0:03:31 how to rotate the values on the y-axis of a histogram in R using the "las" argument 0:03:39 how to add a "density curve" to a histogram in R using the "lines" command 0:04:00 how to change the color of the density curve in a histogram in R using the "col" argument 0:04:07 how to change the width of the density curve in a histogram in R using the "lwd" argument ♠︎♣︎♥︎♦︎To learn more: Subscribe: https://goo.gl/4vDQzT website: http://statslectures.com Facebook:https://goo.gl/qYQavS Twitter:https://goo.gl/393AQG Instagram: https://goo.gl/fdPiDn Our Team: Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at UBC. Producer: Ladan Hamadani (B.Sc., BA., MPH) These #RTutorial are created by #marinstatslectures to support the statistics course (#SPPH400) at The University of British Columbia(UBC) although we make all videos available to the public for free.
Making Boxplots and Boxplots With Groups in R (R Tutorial 2.2)
 
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How to produce box plots (a.k.a. box and whisker diagram) in R, as well as "side by side boxplots" for multiple groups (i.e. boxplots with groups). This tutorial explains how to add titles, change axes labels, and many other modifications to the plot by using "boxplot", "~", "ylim", and "quantile" commands and "xlab", "ylab", "ylim", "las" arguments. This video is a tutorial for programming in R Statistical Software for beginners. You can access and download the "LungCapData" dataset here: Website: http://www.statslectures.com/index.php/r-stats-datasets OR Excel format: https://bit.ly/LungCapDataxls Tab Delimited Text File: https://bit.ly/LungCapData Here is a quick look at the topics addressed in this video; use the timestamps to jump anywhere in the video 0:00:05 what is a box plot and when should we use it for our data 0:00:25 how to produce a "box plot" in R using "box.plot" command 0:00:30 how to access the help menu in R 0:00:51 what is a "box plot"? 0:00:56 how to report the "minimum", "first quartile", "median", "third quartile", and "maximum" in a "box plot" in R using the "quantile" command Modifying Box Plots in R 0:01:31 how to add a title to a boxplot in R using the "main" argument 0:01:39 how to label the x-axis or the y-axis of a "box plot" using "xlab" or "ylab" arguments 0:01:52 how to change the limits for the y-axis of a "box plot" in R using the "ylim" argument 0:02:04 how to rotate the values on the y-axis of a "box plot" using "las" argument 0:02:13 how to produce side-by-side box plots in R using "boxplot" and "~" (separate) commands (for example: when comparing the distribution of a numeric variable for different groups that are formed by a categorical variable) 0:02:53 how to add a title to side-by-side boxplots in R using the "main" argument 0:03:04 how to produce side-by-side box plots in R using the "square brackets" to subset data 0:03:35 double equal sign (==) , what does this mean?
Getting started with R: Basic Arithmetic and Coding in R | R Tutorial 1.3 | MarinStatsLectures
 
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Getting started with R: Basic Arithmetic and Coding in R; Download & Setup R and RStudio https://youtu.be/cX532N_XLIs More Statistics and R Programming Tutorials: https://goo.gl/4vDQzT How to assign values to objects in R, How to turn R into a fancy calculator and perform basic arithmetic functions (+, -, *, /) in R, and more. ▶︎▶︎In this R tutorial you will learn: ▶︎How to assign values to object is R using the equal sign (=) or less than sign with dash ▶︎ How to use ls function to see the data sets stored in R ▶︎use rm function to remove an object in R ▶︎How to add, subtract, multiply,and divide in R ▶︎ How to use sqrt function in R to find the square root of an object ▶︎ How to use log function in R to calculate algorithms, ▶︎ How to use exp function in R to take the exponent or anti-log ▶︎ How to use abs function in R to calculate the absolute value ▶︎ and a few handy keyboard shortcuts in R Watch More: ▶︎Starting with R Tutorials https://bit.ly/2zaFd5b ▶︎Graphs and Descriptive Statistics in R: https://bit.ly/2PkTneg ▶︎Probability Distributions in R: https://bit.ly/2AT3wpI ▶︎Bivariate Analysis in R: https://bit.ly/2SXvcRi ▶︎Linear Regression in R: https://bit.ly/1iytAtm ▶︎Intro to Statistics Course: https://bit.ly/2SQOxDH ◼︎ Topics in the video: 0:00:20 How to assign values to an object in R 0:01:46 How to use "ls" function to see what is stored in R 0:01:57 How to remove an object using "rm" command 0:02:52 How to assign character values to objects in R 0:03:37 How to do basic arithmetic in R 0:04:50 How to take the square root of an object in R 0:05:07 How to use the "log" function in R 0:05:12 How to take the exponent or anti-log using "exp" function in R 0:05:30 How to calculate the absolute value using the "abs" function in R 0:06:14 a few handy keyboard shortcuts in R 0:06:41 Including comments and notes to self within code in R This video is a tutorial for programming in R Statistical Software for beginners, using RStudio. Follow MarinStatsLectures Subscribe: https://goo.gl/4vDQzT website: https://statslectures.com Facebook:https://goo.gl/qYQavS Twitter:https://goo.gl/393AQG Instagram: https://goo.gl/fdPiDn Our Team: Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at UBC. Producer and Creative Manager: Ladan Hamadani (B.Sc., BA., MPH) These videos are created by #marinstatslectures to support a course at The University of British Columbia (UBC) (SPPH400: #IntroductoryStatistics and #RTutorial for Health Science Research), although we make all videos available to the public for free. Thanks for watching! Have fun and remember that statistics is almost as beautiful as a unicorn!
Poisson Distribution in R (R Tutorial 3.2)
 
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Learn how to calculate probabilities for Poisson Random Variables in R. You will learn to use "ppois", "dpois", and the "sum" command. This video is a tutorial for programming in R Statistical Software for beginners. Here is a quick overview of the topics addressed in this video: 0:00:08 introducing the poisson random variable that was used in this video and its characteristics 0:00:18 how to calculate probabilities for the poisson distribution in R using the "ppois" or "dpois" command 0:00:28 how to access help menu in R for calculating probabilities for poisson distribution 0:00:39 how to find values for the probability density function of X in R using "dpois" command 0:01:16 how to have R return multiple probabilities for a poisson distribution using the "dpois" command 0:02:02 how to calculate cumulative probabilities for a poisson distribution in R using the "sum" command 0:02:26 how to have R return to us the cumulative probabilities (of equal or smaller than) for a poisson distribution using the probability distribution function and "ppois" command and lower tail probability 0:03:10 how to have R return to us the cumulative probabilities (of equal or greater than) for a poisson distribution using the probability distribution function and "ppois" command and upper tail probability 0:03:36 "rpois" command to take random sample from a poisson distribution 0:03:44 "qpois" command to find quantiles for a poisson distribution
Wilcoxon Signed Rank Test in R (R Tutorial 4.5)
 
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Learn how to conduct the Wilcoxon Signed Rank test in R. This test is the non-parametric alternative to the paired t-test. We will discuss the "wilcox.test", "boxplot", "exact", "alt", "conf.int", and "correct" commands in R. This video is a tutorial for programming in R Statistical Software for beginners. To access and download dataset: For Tab Delimited Data File: https://bit.ly/BloodpressureTXT For Excel file: http://bit.ly/BloodPressureXLS Here is a quick overview of the topics addressed in this video: 0:00:08 When is it appropriate to use "Wilcoxon Signed Rank Test" 0:00:53 how to access the Help menu in R for Wilcoxon Signed Rank Test 0:01:04 how to examine the data visually in R using "boxplot" command 0:01:20 how to perform Wilcoxon Signed Rank Test in R using the "wilcox.test" command 0:01:42 how to test the difference in medians is 0 for the Wilcoxon Signed Rank Test suing "mu" argument 0:01:49 how to have a two-sided test or two-sided alternative for the Wilcoxon Signed Rank Test by using the "alt" argument 0:01:58 how to let R know that the two populations are paired or dependent using "paired" argument 0:02:07 how to ask R to return a confidence interval for the Wilcoxon Signed Rank Test using "conf.int" argument 0:02:14 how to specify the confidence level in R for the Wilcoxon Signed Rank Test using "conf.level" argument 0:02:40 how to ask R to calculate an approximate p-value and an approximate confidence interval for the Wilcoxon Signed Rank Test using "exact" argument 0:02:54 how to ask R to not use a continuity correction for the Wilcoxon Signed Rank Test using "correct" argument
Stem and Leaf Plots in R (R Tutorial 2.4)
 
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Learn how to produce a "stem and leaf plot" using the "stem" command and adjust the scale for it using the "scale" argument. This video is a tutorial for programming in R Statistical Software for beginners. You can access and download the "LungCapData" dataset here: Website: http://www.statslectures.com/index.php/r-stats-datasets OR: Excel format: https://bit.ly/LungCapDataxls Tab Delimited Text File: https://bit.ly/LungCapData Here is a quick look at the topics addressed in this video: 0:00:05 when is it appropriate to use "Stem and Leaf Plots" for our data? 0:00:33 how to produce the stem and leaf plot in R using the "stem" command 0:00:41 how to access help menu in R for stem and leaf plots 0:01:16 how to adjust the scale on the stem and leaf plot in R using the "scale" argument
Paired t Test in R (R Tutorial 4.4)
 
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Learn how to conduct the matched paired t-test in R. This test is used to compare the means of two paired or dependent populations. We will discuss the "t.test" , "paired", "conf.level", "boxplot" and other commands in R for beginners. This video is a tutorial for programming in R Statistical Software. To access and download dataset: For Tab Delimited Data File: https://bit.ly/BloodpressureTXT For Excel file: http://bit.ly/BloodPressureXLS Here is a quick overview of the topics addressed in this video: 0:00:09 When is it appropriate to use the paired t-test and confidence interval to analyze the data 0:00:55 how to access the help menu in R for paired t-test 0:01:05 how to visualize and interpret the difference in means for two populations that are paired or dependent on one another in R using "boxplot" command 0:01:21 how to visualize the data as paired or the changes in individuals in R using the "scatterplot" command 0:01:39 how to add a line for X=Y (eg. before= after) in a paired data plot using the "abline" command 0:01:58 how to interpret the scatterplot of paired or dependent data 0:02:32 how to do the paired t-test in R using the "t.test" command 0:02:40 how to let R know to test if the mean difference is 0 in a paired t-test using the "mu" argument 0:02:47 how to have a two-sided t-test in R using the "alt" argument 0:02:54 how to let R know that the data is paired when conducting t-test using "paired" argument 0:03:02 how to specify the level of confidence interval in R for the paired t-test using the "conf.level" argument 0:03:35 how does the order that X and Y are entered in "t.test" command in R for a paired-t-test changes the results
Logic Statements (TRUE/FALSE) and cbind and rbind Functions in R (R Tutorial 1.9)
 
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Learn how logic commands can be used in R to identify observations with certain attributes and return a true/false, based on values of other variables in a dataset. You will learn the "as.numeric" & "cbind" commands. This video is a tutorial for programming in R Statistical Software for beginners. You can access and download the "LungCapData" dataset from our Website: http://www.statslectures.com/index.php/r-stats-datasets OR Excel format: https://bit.ly/LungCapDataxls Tab Delimited Text File: https://bit.ly/LungCapData Here is an overview of the topics discussed in this video. 0:00:48 how to create a logical vector or variable in R Statistical Software 0:01:15 how to turn True or False indicators into 0's and 1's in R using "as.numeric" command 0:01:55 how to use multiple logical statements within an R command to have a logical vector answering multiple questions (step by step example) 0:02:50 how to attach vectors or matrices in a column-wise fashion using the "cbind" command or in a row-wise fashion using the "rbind" command in R 0:03:43 two different ways of cleaning R's workspace: using RStudio's menu or "rm" command
Create and Work with Vectors and Matrices in R | R Tutorial 1.4 | MarinStatslectures
 
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Create and Work with Vectors and Matrices in R; Import Excel Data into R Tutorial https://bit.ly/2OMBdga More Statistics and R Programming Tutorials: https://goo.gl/4vDQzT How to Create, Modify and Work with Vectors and Matrices in R ▶︎▶︎Reminder: One of the important features of R is that it can handle complex statistical operations in an easy and efficient way. R handles complex computations using Vectors, Matrices, Lists, Dataframes and Datasets; In this video we focus on Vectors and Matrices in R. In R, Vector is a basic data structure that contains element of similar type (logical, integer, double, character, complex or raw). A matrix is basically a two-way generalization of a vector. Instead of a single index, we can use two indexes, one representing a row and the second representing a column. ▶︎▶︎In this R tutorial you will learn: ▶︎ How to create vectors in R for numbers or objects using the c function or concatenate function ▶︎ How to use seq function to create sequence data in R ▶︎ How to use rep function in R to create a vector of repeated numbers or characters ▶︎ How to create a matrix using matrix function in R and use square brackets to extract certain elements from a matrix in R ▶︎ How to perform basic arithmetic functions on the elements of one vector, preform arithmetic functions on the corresponding elements of two vectors and perform element-wise arithmetic functions in a matrix in R Statistical software. This video is a tutorial for programming in R Statistical Software for beginners. ◼︎ Topics in the video: 0:00:29 How to create vectors in R for both numbers or objects using the "c" or "concatenate" function 0:01:09 How to create a sequence of integer values in R using the colon (:) 0:01:20 How to use "seq" function in R to create sequences 0:01:55 How to use "rep" function in R to create a vector of repeated numbers or characters 0:03:34 How to perform basic arithmetic functions on the elements of one vector in R 0:04:02 How to preform arithmetic functions on the corresponding elements of two vectors in R 0:04:59 How to extract elements of a vector using square brackets[] in R 0:06:08 How to create a matrix using "matrix" function in R 0:06:21 How to set the number of rows and columns in a matrix using "nrow" and "byrow" functions in R 0:07:05 How to use the square brackets to extract certain elements from a matrix in R 0:08:06 How to perform element-wise arithmetic functions in a matrix in R Watch More: ▶︎Starting with R Tutorials https://bit.ly/2zaFd5b ▶︎Graphs and Descriptive Statistics in R: https://bit.ly/2PkTneg ▶︎Probability Distributions in R: https://bit.ly/2AT3wpI ▶︎Bivariate Analysis in R: https://bit.ly/2SXvcRi ▶︎Linear Regression in R: https://bit.ly/1iytAtm ▶︎Intro to Statistics Course: https://bit.ly/2SQOxDH This video is a tutorial for programming in R Statistical Software for beginners, using RStudio. Follow MarinStatsLectures Subscribe: https://goo.gl/4vDQzT website: https://statslectures.com Facebook:https://goo.gl/qYQavS Twitter:https://goo.gl/393AQG Instagram: https://goo.gl/fdPiDn Our Team: Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at UBC. Producer and Creative Manager: Ladan Hamadani (B.Sc., BA., MPH) These videos are created by #marinstatslectures to support a course at The University of British Columbia (UBC) (SPPH400: #IntroductoryStatistics and #RTutorial for Health Science Research), although we make all videos available to the public for free. Thanks for watching! Have fun and remember that statistics is almost as beautiful as a unicorn!
Categorical Variables or Factors in Linear Regression in R (R Tutorial 5.7)
 
05:42
Learn how to include a categorical variable (a factor or qualitative variable) in a regression model in R. You will also learn how to interpret the model coefficients. The video provides a tutorial for programming in R Statistical Software for beginners. You can access and download the "LungCapData" dataset here: Excel format: https://bit.ly/LungCapDataxls Tab Delimited Text File: https://bit.ly/LungCapData Here is a brief overview of the topics addressed in this video:
Change Reference/Baseline Category for a Categorical Variable in Regression Model (R Tutorial 5.6)
 
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Learn how to change the reference/baseline category for a categorical variable (a factor or qualitative variable) in a linear regression model in R. In this video you will learn how to use "relevel" command in R. The video provides a tutorial for programming in R Statistical Software for beginners. You can access and download the "LungCapData" dataset here: Excel format: https://bit.ly/LungCapDataxls Tab Delimited Text File: https://bit.ly/LungCapData Here is a brief overview of the topics addressed in this video: 0:00:13 what is the interpretation of the intercept or constant term? 0:00:21 what is the interpretation of the model coefficients or parameters? 0:00:46 what is the command used to change the reference or baseline category of a categorical variable? 0:00:51 how to access the help menu in R 0:01:01 how to fit a linear regression model in R relating one outcome variable to two explanatory variables 0:01:21 how to interpret the fitted regression model output and model coefficients or parameters in R 0:01:26 how to interpret the model intercept 0:01:39 how to interpret the model coefficient for a numeric variable 0:01:56.5 how to interpret the model coefficient for a categorical variable 0:02:25 how to change the reference or baseline group in R 0:02:31 how does R choose the reference or baseline category? 0:02:50 how to use the "relevel" command to change the reference or baseline category in R 0:03:15 fit a model where we have changed the reference category
Importing , Checking and Working with Data in R | R Tutorial 1.7 | MarinStatsLectures
 
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Importing Data, Checking the Imported Data and Working With Data in R; Dataset: https://goo.gl/tJj5XG More Statistics and R Programming Tutorials: https://goo.gl/4vDQzT How to import a datasets into R , How to make sure data was imported correctly into R and How to begin to work with the imported data in R. ▶︎We will learn to use read.table function (which reads a file in table format and creates a data frame from it, with cases corresponding to lines and variables to fields in the file), and some of the arguments such as header argument and sep argument. ▶︎We will learn to use file.choose function to choose a file interactively ▶︎We will discuss how to use Menu options in RStudio to import data into R ▶︎and how to check the imported data to make sure it was imported correctly into R using the dim function to retrieve dimension of an object and let you know the number of rows and columns of the imported data, the head function in R (head() function), which returns the first or last parts of a vector, matrix, table, data frame and will let you see the first several rows of the data, the tail function in R (tail() function) to see the last several rows of the data in R, the double square brackets in R to subset data (brackets lets you select or subset data from a vector, matrix, array, list or data frame) , and the names function in R to get the names of an object in R. ▶︎▶︎ Download the dataset here: https://statslectures.com/r-stats-datasets ▶︎▶︎Watch More ▶︎Export Data from R (CSV , TXT and other formats): https://bit.ly/2PWS84w ▶︎Graphs and Descriptive Statistics in R: https://bit.ly/2PkTneg ▶︎Probability Distributions in R: https://bit.ly/2AT3wpI ▶︎Bivariate Analysis in R: https://bit.ly/2SXvcRi ▶︎Linear Regression in R: https://bit.ly/1iytAtm ▶︎Intro to Statistics Course: https://bit.ly/2SQOxDH ◼︎ Topics in the video: 0:00:07 How to read a dataset into R using read.table function and save it as an object 0:00:27 How to access the help menu in R 0:01:02 How to let R know that the first row of our data is headers by using header argument 0:01:14 How to let R know how the observations are separated by using sep argument 0:02:03 How to specify the path to the file using file.choose function 0:03:15 How to use Menu options in R Studio to import data into R 0:05:23 How to prepare the Excel data for importing into R 0:06:15 How to know the dimensions (the number of rows and columns) of the data in R using the dim function 0:06:35 How to see the first several rows of the data using the head command in R 0:06:45 How to see the last several rows of the data in R using the tail function 0:07:18 How to check if the data was read correctly into R using square brackets and subsetting data 0:08:21 How to check the variable names in R using the names function This video is a tutorial for programming in R Statistical Software for beginners, using RStudio. Follow MarinStatsLectures Subscribe: https://goo.gl/4vDQzT website: https://statslectures.com Facebook:https://goo.gl/qYQavS Twitter:https://goo.gl/393AQG Instagram: https://goo.gl/fdPiDn Our Team: Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at UBC. Producer and Creative Manager: Ladan Hamadani (B.Sc., BA., MPH) The #RTutorial is created by #marinstatslectures to support the statistics course (SPPH400 #IntroductoryStatistics) at The University of British Columbia(UBC) although we make all videos available to the everyone everywhere for free! Thanks for watching! Have fun and remember that statistics is almost as beautiful as a unicorn!
Bar Charts and Pie Charts in R | R Tutorial 2.1| MarinStatsLectures
 
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Bar Chart and Pie Charts in R; For more Statistics and R Programming Tutorials: https://goo.gl/4vDQzT - Sample vs Population (Histograms vs Probability Distributions) Statistics Tutorial: https://youtu.be/DOnucdP7LNU - Dataset: https://goo.gl/tJj5XG How to produce "bar charts" and "pie charts" in R, add titles, change axes labels, and many other modifications to these plots. This tutorial explains how to use "table", "barplot", and "pie" commands and "main", "lab", "las", "names.arg", "horiz" arguments. This video is a tutorial for programming in R Statistical Software for beginners. ►►You can access and download the dataset here: https://statslectures.com/r-stats-datasets here is a quick look at the topics in the video; use the timestamps to jump to topics in the video 0:00:07 when to use barcharts and piecharts for your data 0:00:29 how to produce a bar chart in R using "barplot" command 0:00:35 how to access the help menu in R 0:00:49 what is a "bar chart" and when is it appropriate to use a "bar chart"? 0:01:02 how to produce frequency table in R using "table" command Modifying Bar Charts in R: 0:02:41 how to add a tile to a bar chart in R using the "main" argument 0:02:48 how to add labels to x and y axes of a bar chart in R using "lab" argument 0:03:02 how to rotate the values on the y-axis in R using the "las" argument 0:03:11 how to change the names or labels appearing under each of the bars in R using "names.arg" argument 0:03:34 how to make bars appear horizontally rather than vertically in R using "horiz" argument Modifying Pie Chart in R: 0:04:07 how to produce a pie chart in R using "pie" command. 0:04:15 how to add a title to a pie chart in R using the "main" argument 0:04:24 how to add a box around a pie chart in R using "box" command ♠︎♣︎♥︎♦︎To learn more: Subscribe: https://goo.gl/4vDQzT website: http://statslectures.com Facebook:https://goo.gl/qYQavS Twitter:https://goo.gl/393AQG Instagram: https://goo.gl/fdPiDn Our Team: Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at UBC. Producer: Ladan Hamadani (B.Sc., BA., MPH) These #RTutorial are created by #marinstatslectures to support the statistics course (#SPPH400) at The University of British Columbia(UBC) although we make all videos available to the public for free.
Scripts for Reproducible Research in R (R Tutorial 1.11)
 
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Learn how to work with scripts in R and how to submit commands to R console from the RStudio's Source(Script) Editor. You will also learn very handy keyboard short-cuts, and the use of the tab key. This video is a tutorial for programming in R Statistical Software for beginners. Here is an overview of the topics discussed in this video. You can click on the time stamp to jump to the specific topic. 0:00:07 What is a script in R and why use them 0:00:40 writing scripts in R using copy/paste for a text editor 0:00:55 writing scripts in R using RStudio's Source Editor 0:01:07 how to create a new script in RStudio's Source Editor using menu options 0:01:19 how to open existing scripts in RStudio's Source Editor using menu options 0:01:56 how to submit a line of code into R Console from RStudio's Source Editor without copy and paste 0:02:21 how to use keyboard shortcuts to submit a line of code in R 0:03:08 getting to know various functionality of RStudio Source(Script) Editor 0:04:09 how to fix a typo in the script of codes in R 0:04:25 how to use the "tab" key (on keyboard) in RStudio Source Editor to help with the name of a command
Stacked Bar Charts, Grouped Bar Charts and Mosaic Plots in R (R Tutorial 2.5)
 
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Learn how to produce and customize "stacked bar charts", "clustered bar charts" and "mosaic plots" for examining the relationship between two categorical variables in R. You will learn to use the "table", "barplot", "mosaicplot", "beside",and "legend" commands. This video is a tutorial for programming in R Statistical Software for beginners. You can access and download the "LungCapData" dataset here: Excel format: https://bit.ly/LungCapDataxls Tab Delimited Text File: https://bit.ly/LungCapData Here is a quick look at topics that are addressed in this video: 0:00:09 when is it appropriate to use "stacked bar charts", "clustered bar charts" and "mosaic plots" for our data 0:00:34 how to produce "stacked bar charts" in R using the "barplot" command 0:00:37 how to access the Help menu for "bar charts" in R 0:00:48 how to produce "contingency table" in R using the "table" command 0:01:22 how to produce "clustered bar charts" in R using "beside" argument 0:01:39 how to express the "bar chart" in terms of "conditional probabilities" 0:02:02 how to add a legend to "bar chart" using the "legend.text" argument 0:02:35 how to add a title to "bar chart" in R using the "main" argument 0:02:44 how to label the x-axis or y-axis of a "bar chart" using the "xlab" or "ylab" arguments 0:02:55 how to rotate the values on the y-axis of a "bar chart" by using the "las" argument 0:03:03 how to change the colours (color) of the bars in "bar chart" in R using the "col" argument 0:03:17 how to produce a "mosaic plot" in R using the "mosaicplot" command
Polynomial Regression in R | R Tutorial 5.12 | MarinStatsLectures
 
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Polynomial Regression in R: How to fit polynomial regression models in R; Download Dataset & R Script:https://goo.gl/tJj5XG More Statistics and R Programming Tutorials here: https://goo.gl/4vDQzT Complete Linear Regression Playlist: Coming soon How to fit polynomial regression models in R and assess polynomial regression models using the partial F-test with R. Polynomial regression is a form of regression analysis in which the relationship between the independent variable X and the dependent variable Y is modelled as an nth degree polynomial in x. Polynomial regression models are useful when the relationship between the independent variables(X) and the dependent variables(Y) is not linear. Download LungCapData2 Dataset and Polynomial Regression R Script http://statslectures.com/index.php/r-stats-datasets Table of Content: coming soon This video provides a tutorial for programming in R Statistical Software and RStudio for beginners. Watch More: Intro to Statistics Course: https://bit.ly/2SQOxDH Getting Started with R: https://bit.ly/2PkTneg Graphs and Descriptive Statistics in R: Probability distributions in R: https://bit.ly/2AT3wpI Bivariate analysis in R: https://bit.ly/2SXvcRi Linear Regression in R: https://bit.ly/1iytAtm ANOVA series https://bit.ly/2zBwjgL Follow MarinStatsLectures Subscribe: https://goo.gl/4vDQzT website: https://statslectures.com Facebook:https://goo.gl/qYQavS Twitter:https://goo.gl/393AQG Instagram: https://goo.gl/fdPiDn Our Team: Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at UBC. Producer and Creative Manager: Ladan Hamadani (B.Sc., BA., MPH) The #RTutorial is created by #marinstatslectures to support the statistics course (SPPH400 #IntroductoryStatistics) at The University of British Columbia(UBC) although we make all videos available to the everyone everywhere for free! Thanks for watching! Have fun and remember that statistics is almost as beautiful as a unicorn!
Multiple Linear Regression with Interaction in R (R Tutorial 5.9)
 
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Learn how to include interaction or effect modification in a regression model in R. You will also learn how to interpret the model coefficients. The video provides a tutorial for programming in R Statistical Software for beginners. You can access and download the "LungCapData" dataset here: Excel format: https://bit.ly/LungCapDataxls Tab Delimited Text File: https://bit.ly/LungCapData You can access and download the R code here: Click here to open with R : http://bit.ly/1H4RLWr Click here for the text file: http://bit.ly/1JK7QXF
Interpreting Interaction in Linear Regression (Tutorial 5.10)
 
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Learn how to interpret interaction or effect modification in a linear regression model, between two factors (two categorical variables). This video does not discuss fitting the model using R, but only discusses how interacting variables are interpreted in a regression model. The previous video (Tutorial 5.9) in the series describes how to fit an interaction term in a linear regression model in R. Here is a brief overview of the topics included in this video: 0:00:16 An introduction to our data that includes one dependent variable and 2 explanatory or independent variables 0:00:43 the visual representation of the data by using a plot 0:01:22 explaining the concept of interaction on the plot 0:02:05 different ways of stating interaction in the data 0:02:25 examining interaction numerically by examining the fitted regression model 0:05:29 examining a model with no interaction 0:06:03 terms for including an interaction term in our model For more videos and datasets used in the videos check our website: http://www.statslectures.com
Correlation and Covariance in R (R Tutorial 4.9)
 
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Learn how to calculate "Pearson's", "Spearman's rank" and "Kendall's rank" correlation and create "confidence intervals" and "hypothesis tests" using "cor" and "cor.test" command. Also learn how to calculate covariance using "cov" command, produce pairwise plots using "pairs" command and a correlation or covariance matrix using the "cor" and "cov" commands. This video provides a beginner introduction to programming in R Statistical Software. You can access and download the "LungCapData" dataset here: Excel format: https://bit.ly/LungCapDataxls Tab Delimited Text File: https://bit.ly/LungCapData Here is a quick overview of the topics addressed in this video: 0:00:08 what is "Pearson's correlation" 0:00:16 what is "Spearman's rank correlation" 0:00:24 what is "kendall's rank correlation" 0:00:54 how to access the help menu in R for correlation commands 0:01:05 how to produce a scatterplot in R to explore the relationship between variables using "plot" command 0:01:39 how to calculate the correlation between variables using the "cor" command 0:01:46 how to calculate "pearson's correlation" in R using "method" command 0:02:17 how to calculate "Spearman's rank correlation" in R using "method" argument 0:02:24 how to calculate "kendall's rank correlation" in R using "method" argument 0:02:34 how to produce a confidence interval and test the hypothesis for the correlation using the "cor.test" command 0:03:21 how to calculate the "p value" when there are exact values in dataset using "exact" argument 0:03:42 how to change the alternative hypothesis using the "alt" argument 0:04:03 how to change confidence level using the "conf.level" command 0:04:13 how to calculate the covariance in R using the "cov" command 0:04:27 how to produce all possible pair-wise plots using the "pairs" command 0:04:50 how to produce a "pairs" plot only for some of the variables in the dataset by sub-setting data using square brackets 0:05:26 how to produce a correlation matrix using the "cor" command and "method" argument 0:05:37 how to deal with categorical variables in the dataset when creating correlation matrix by subsetting data using square brackets 0:06:18 how to produce the covariance matrix using the "cov" command
Changing a Numeric Variable to Categorical Variable in R (R Tutorial 5.4)
 
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Learn how to create a categorical variable (a factor or qualitative variable) from a numeric variable in R using the "cut" command. In this video you will also learn how to label the categories and make the intervals left-closed or right-opened using the "labels" and "right" arguments. The video provides a tutorial for programming in R Statistical Software for beginners. You can access and download the "LungCapData" dataset here: Website: http://www.statslectures.com/index.php/r-stats-datasets Or: Excel format: https://bit.ly/LungCapDataxls Tab Delimited Text File: https://bit.ly/LungCapData Here is a quick overview of the topics discussed in this video; use the timestamps to jump ahead in the video... 0:00:08 What are the reasons to convert a numeric variable into a categorical variable or a factor 0:00:44 How to use the "cut" command in R to convert a numeric variable into a categorical variable 0:00:53 How to access the help menu for the “cut” command in R 0:01:21 How to specify the break points for the new categorical variable in R 0:01:51 How does R treat the border observations in a categorical variable 0:02:08 How to name or label the categories that we created in R using the “labels” argument 0:02:57 How to change the way R treats the border observation in a categorical variable so that the intervals are left-closed or right-opened using the "right" argument within the "cut" command. 0:03:33 How does R label the categories in the new categorical variable by default 0:04:43 How to tell R to create a certain number of categories or levels rather than specifying the break points ourselves
Customizing The Look of R Studio (R Tutorial 1.13)
 
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Learn how to change preferences in RStudio from the default values. These include changing the default working directory, the screen layout, fonts, and much more. This video is a tutorial for programming in R Statistical Software for beginners. 0:00:11 how to change preferences in RStudio using "Tools" menu 0:00:29 how to use the "RStudio" menu in Mac to change preferences 0:00:35 how to set a default workspace in R or restore a previous workspace image 0:01:02 how to change the appearance of code and scripts in R (for example font, font size, colour/color, highlights, quotations, etc.) 0:01:57 how to change the layout of RStudio's interface 0:02:39 how to choose a default mirror for installing packages in R 0:02:58 menu option to save R output into a latex document 0:03:09 how to select the language and dictionaries in R
Two-Sample t Test in R: Independent Groups (R Tutorial 4.2)
 
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Learn how to conduct the independent two-sample t-test and confidence interval for the difference in means of two populations. You will learn to use "t.test", "boxplot", "var.eq" and "leveneTest" command. This video is a tutorial for programming in R Statistical Software for beginners. You can access and download the "LungCapData" dataset here: Excel format: https://bit.ly/LungCapDataxls Tab Delimited Text File: https://bit.ly/LungCapData here is a quick look at the topics addressed in the video: 0:00:10 when is it appropriate to conduct the "independent two sample t-test" and "confidence interval 0:00:53 how to access the help menu in R for t-test 0:01:04 how to visually examine the relationship between the two variables in R before conducting the t-test 0:01:18 how to conduct an independent two-sided t-test with non-equal population variances in R using the "t.test" command 0:01:56 the null and alternative hypothesis, the confidence interval, and variance assumption for our example 0:03:06 how to use the "mu" argument in two-sided t-test 0:03:12 how to use the "alt" argument in order to do a one-sided t-test 0:03:18 how to use the "conf" argument in order to change the confidence level for the t-test 0:03:24 how to use the "var.eq" argument in order to assume equal population variances for t-test 0:03:29 how to let R know that groups are paired or dependent using the "paired" argument 0:03:37 two different ways for separating the groups in "t.test" command in R 0:04:18 how to decide if we want to assume equal or non equal variances using boxplot 0:04:38 how to decide if we want to assume equal or non equal variances comparing the actual variances 0:05:02 how to test the null hypothesis "that the population variances are equal" using Levene's test using "leveneTest" command
How to Install Packages in R (R Tutorial 1.12)
 
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Learn how to find and install packages for R, using the "install.packages" command or menu options in RStudio. This video is a tutorial for programming in R Statistical Software for beginners. Here is an overview of the topics discussed in this video. You can click on the time stamp to jump to the specific topic. 0:00:12 what are packages in R and why use them 0:00:46 how to access help menu for packages in R when using the "install.packages" command 0:01:00 how to install packages in R using "install.packages" command when you know the name of the package 0:01:53 how to install packages in R using "install.packages" command when you don't know the name of the package 0:02:48 how to load the library of commands and functions for a package in R 0:03:17 how to access and download packages for R from 'R-project.org' website 0:04:30 how to access help menu for a specific package in R 0:04:57 how to remove a package from R using "remove.packages" command 0:05:11 how to install packages in R using the menus in RStudio
Scatterplots in R (R Tutorial 2.6)
 
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How to make scatterplot in R to examine the relationship between two numeric variables. This tutorial explains how to use the "plot", "cor", "abline", "spline," "lty" and "lines" command. This video is a tutorial for programming in R Statistical Software for beginners. You can access and download the "LungCapData" dataset here: Excel format: https://bit.ly/LungCapDataxls Tab Delimited Text File: https://bit.ly/LungCapData Here is a quick overview of the topics addressed in this video: 0:00:04 when is it appropriate to use "scatterplot" for our data 0:00:27 how to produce a scatterplot in R using the "plot" command 0:00:34 how to access the help menu in R for scatterplots 0:00:42 how to calculate "pearson's correlation" in R using the "cor" command 0:01:09 how to determine which variable appears on which axes of a scatterplot in R 0:01:24 how to add a title to a scatterplot in R using the "main" argument 0:01:28 how to add labels to the axes of a scatterplot in R using the "xlab" or "ylab" arguments 0:01:46 how to rotate values of y-axis of a scatterplot in R using "las" argument 0:01:55 how to change limits of x-axis or y-axis of a scatterplot in R using "xlim" or "ylim" argument 0:02:10 how to change the size of the plotting characters of a scatterplot in R using the "cex" argument 0:02:26 how to change the shape of the plotting character of a scatterplot in R using the "pch" argument 0:02:50 how to change the color of the characters of a scatterplot in R using the "col" argument 0:03:01 how to add a regression line to a scatterplot in R using "abline" command 0:03:22 how to change the colour (color) of a regression line in R using the "col" argument 0:03:34 how to add a nonparametric smoother to the scatterplot in R using the "lines" and "smooth.spline" command 0:04:06 how to change the line type that we're plotting using the "lty" argument 0:04:13 how to change the width of the line we are plotting using the "lwd" argument
Sensitivity, Specificity, Positive Predictive Value and Negative Predictive Value
 
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In this video, we explain the concepts and calculations of sensitivity, specificity, false positive, false negative, positive predictive value and negative predictive value, as they apply to screening and/or diagnostic testing.
Setting Up Your Working Directory in R (R Tutorial 1.10)
 
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Setting up a working directory for a project in R. Find more #Statistics and #RStats Tutorials here: https://goo.gl/4vDQzT ▶︎In this tutorial, You will learn to use the "getwd", "setwd", "save.image", and "load" commands. This video is a tutorial for programming in #RStatistical Software for beginners. You can access and download the "#LungCapData" dataset from our website: http://www.statslectures.com/index.php/r-stats-datasets OR Excel format: https://bit.ly/LungCapDataxls Tab Delimited Text File: https://bit.ly/LungCapData Here is an overview of the topics discussed in this video. 0:00:07 what are "working directories" in R Statistical Software and why use them 0:00:49 how to find the current working directory in R using the "getwd" command 0:01:03 how to set a working directory in R using "setwd" command 0:02:15 how to set up working directories in R using RStudio menu items 0:03:26 how to save the current "workspace image" in R using the "save.image" command 0:04:38 how to let R know that a file is a workspace image using ".Rdata" extension 0:04:55 how to use the menu items in #RStudio to save a workspace image 0:05:32 how to remove all items from the current workspace using the ("rm(list=ls()") command 0:05:42 how to remove all items from the current workspace using RStudio menus 0:05:54 how to quit R using RStudio menus 0:05:58 how to quit R using "q" command 0:07:05 how to load the previous workspace image using the "load" command 0:07:30 how to load the previous workspace image using the "file.choose" command 0:07:51 how to load the previous workspace image using RStudio menus *****************************************************************************************To learn more: Subscribe: https://goo.gl/4vDQzT website: http://statslectures.com Facebook:https://goo.gl/qYQavS Twitter:https://goo.gl/393AQG Instagram: https://goo.gl/fdPiDn Our Team: Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at #UBC. Producer: Ladan Hamadani (B.Sc., BA., MPH)
Hypothesis Testing 2: null and alternative hypothesis (one sample t test)
 
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Learn about the null and alternative hypotheses, and how they are set up in a hypothesis test. This video is the second in a series that introduce the concepts and principles of hypothesis testing, in the context of a one-sample t-test.
Variable Selection in Linear Regression Using Partial F-Test in R (R Tutorial 5.11)
 
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Learn how to use the Partial F-test to compare nested models for regression modelling in R. The Partial F-test is a useful tool for variable selection when building a regression model. You will also learn what the Sum of Square Error is, and its use in The Partial F-test. This video provides a tutorial for programming in R Statistical Software for beginners. You can access and download the "LungCapData" dataset here: Website: http://www.statslectures.com/index.ph... or: Excel format: https://bit.ly/LungCapDataxls Tab Delimited Text File: https://bit.ly/LungCapData
Normal Distribution, Z Scores, and Normal Probabilities in R | R Tutorial 3.3| MarinStatslectures
 
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Normal Distribution, Z Scores, and Normal Probabilities in R; For more Statistics and R Programming Tutorials: https://goo.gl/4vDQzT - Normal Distribution, Standardizing and Their Use Explained https://goo.gl/g9A1i5 How to calculate probabilities, quantiles, percentiles and taking random samples for Normal Random Variables in R. In this R Programming tutorial, you will learn to calculate probabilities for Z scores. You will learn to calculate probabilities for a normal distribution using pnorm command and also use dnorm, rnorm, and qnorm commands in R Software. This R tutorial will also show you how to draw the probability density curve for a normal variable. This video is a tutorial for programming in R Statistical Software for beginners. ♠︎♣︎♥︎♦︎To learn more: Subscribe: https://goo.gl/4vDQzT website: http://statslectures.com Facebook:https://goo.gl/qYQavS Twitter:https://goo.gl/393AQG Instagram: https://goo.gl/fdPiDn Our Team: Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at UBC. Producer: Ladan Hamadani (B.Sc., BA., MPH) These #RTutorial are created by #marinstatslectures to support the statistics course (#SPPH400) at The University of British Columbia(UBC) although we make all videos available to the public for free.
Working with Variables and Data in R | R Tutorial 1.8 | MarinStatslectures
 
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Working with Variables and Data in R and Produce Summaries; Practice with Dataset: https://goo.gl/tJj5XG Install R and RStudio Video https://bit.ly/2PYO8jS More Statistics and R ProgrammingTutorials here: https://goo.gl/4vDQzT How to check variable names, variable types, extract a variable from a dataset, and produce summaries for data based on the type of data in R. ▶︎ How to check variable names for datasets in R? We will use names function in R ▶︎ How to extract a variable from a dataset in R? We will learn to use $ or Attach function in R ▶︎ How to check the variable type (numeric or categorical) in R? We will use class function in R ▶︎ How to ask R for different levels/categories of a categorical variable? levels function in R will be used ▶︎ How to produce summary for variable in R? summary function in R will produce summary of variables based on they type, for example numeric values will be summarized by mean, median and quartiles, and factors or categorical variables will be summarized as frequencies. ▶︎▶︎Download the dataset here: https://statslectures.com/r-stats-datasets ▶︎▶︎Watch More: ▶︎Getting Started with R: https://bit.ly/2PkTneg ▶︎Graphs and Descriptive Statistics in R: https://bit.ly/2PkTneg ▶︎Probability distributions in R: https://bit.ly/2AT3wpI ▶︎Bivariate analysis in R: https://bit.ly/2SXvcRi ▶︎Linear Regression in R: https://bit.ly/1iytAtm ▶︎Intro to Statistics Course: https://bit.ly/2SQOxDH ◼︎ Table of Content 0:01:06 How to use the dollar sign "$" to extract the variable within a dataset in R 0:02:25 How to make objects/variables within a data frame accessible in R? introducing the "attach" function 0:03:20 How too un-attach the data in R? working with the "detach" function 0:04:04 How to check the type or class of a variable in R? using the "class" function in R 0:05:04 How to use the "levels" function in R to find out the different levels/ categories for a factor/categorical data 0:05:34 How to produce summaries for data in R? learn to use the "summary" function in R 0:06:30 How to convert a numeric variable to categorical/factor variable in R using "as.factor" function This video is a tutorial for programming in R Statistical Software for beginners. Follow MarinStatsLectures Subscribe: https://goo.gl/4vDQzT website: https://statslectures.com Facebook:https://goo.gl/qYQavS Twitter:https://goo.gl/393AQG Instagram: https://goo.gl/fdPiDn Our Team: Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at UBC. Producer and Creative Manager: Ladan Hamadani (B.Sc., BA., MPH) These videos are created by #marinstatslectures to support a course at The University of British Columbia (UBC) (SPPH400: #IntroductoryStatistics and #RTutorial for Health Science Research), although we make all videos available to the public for free. Thanks for watching! Have fun and remember that statistics is almost as beautiful as a unicorn!
What is a Confidence Interval?
 
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Learn the concept of a confidence interval, as it applies to a population mean. A Confidence Interval provides a range of possible values for the population mean. This video provides a fun, and conceptual introduction to confidence intervals, and their use in statistical inference. Check out the web visualizations here: http://www.zoology.ubc.ca/~whitlock/kingfisher/CIMean.htm
Hypothesis Testing 1: the big picture (one sample t test)
 
02:07
Learn about the type of questions that motivates the use of a hypothesis test. This video is the first in a series that introduce the concepts and principles of hypothesis testing, in the context of a one-sample t-test. In this set of tutorial you will learn the concept of a null and alternative hypothesis, how a test statistic can be used to measure the compatibility of our data with the null hypothesis, the use of a significance level and p-values or critical regions, conclusions that we can make as well as the errors that may be made when drawing our conclusions. For more videos visit: http://statslectures.com/index.php
One-Sample t Test in R (R Tutorial 4.1)
 
04:40
Learn how to conduct the one-sample t-test and confidence interval for the mean of a single variable. You will learn to use "t.test", "boxplot", "attributes" and "$" commands. This video is a tutorial for programming in R Statistical Software for beginners. You can access and download the "LungCapData" dataset here: Excel format: https://bit.ly/LungCapDataxls Tab Delimited Text File: https://bit.ly/LungCapData Here is a quick overview of the topics addressed in this video: 0:00:11 when is it appropriate to use one sample t-test and confidence interval 0:00:35 how to conduct the one-sample t-test and the confidence interval in R using the "t.test" command 0:00:41 how to access the Help menu in R for the t-test 0:01:05 how to test a null and one-sided alternative hypothesis for the mean with a one-sided confidence interval in R using "t.test" command and "alt" argument 0:02:40 how to produce a two-sided hypothesis test and confidence interval in R, setting the "alternative" ("alt") argument to "two.sided" 0:03:16 how to create a 99 percent confidence interval in R using the "conf" argument 0:03:46 how to see different attributes of an object in R using the "attributes" command 0:03:59 how to extract specific attributes of an object in R using the dollar sign ($)
Calculating Mean, Standard Deviation, Frequencies in R | R Tutorial 2.7| MarinStatsLectures
 
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Calculating Mean, Standard Deviation, Frequencies in R (Descriptive Statistics in R); For more Statistics and R Programming Tutorials: https://goo.gl/4vDQzT - Standard Deviation Explained https://youtu.be/nlm9gfso4mw Learn how to produce numeric summaries for both categorical and numerical variables in R. This tutorial explains how to produce frequency and contingency tables and to calculate mean, median, variance, standard deviation and many more operations using commands such as "table", "mean", "median", "var", "sd", "summary", etc. You can access and download the dataset here: https://statslectures.com/r-stats-datasets Here is a quick overview of the topics addressed in this video: 0:00:36 how to access the Help menu in R for any of the commands 0:00:52 how to summarize a categorical variable 0:00:58 how to produce a "frequency table" in R to summarize a categorical variable using "table" command 0:01:10 how to express the "frequency table" in R using proportion 0:01:18 how to ask R for the number of observations using the "length" commandhttps://youtu.be/nlm9gfso4mw 0:01:51 how to produce a "two-way table" or "contingency table" in R to summarize a categorical variable using "table" command 0:02:09 how to calculate the mean and trimmed mean in R to summarize a numeric variable using "mean" command and "trim" argument 0:02:37 how to calculate the "median" in R to summarize a numeric variable using the "median" command 0:02:45 how to calculate the variance in R to summarize a numeric variable using "var" command 0:02:54 how to calculate the "standard deviation" in R to summarize a numeric variable using the "sd" command or "sqrt" command (taking square root of variance) 0:03:23 how to calculate the minimum, maximum and range in R to summarize a numeric variable using "min", "max" and "range" command 0:03:45 how to calculate specific quantiles or percentiles in R using the "quantile" command and "probs" argument 0:04:53 how to calculate "Pearson's correlation" in R to summarize a numerical variable using the "cor" command 0:05:10 how to calculate "Spearman's correlation" in R to summarize a numerical variable using the "cor" command and "method" argument 0:05:22 how to calculate the covariance in R using the "cov" or "var" command 0:05:43 how to summarize all data (both numeric and categorical) in R using the "summary" command ►►Make sure to check out the Statistics tutorial on Standard Deviation and what it actually measures here: https://youtu.be/nlm9gfso4mw ♠︎♣︎♥︎♦︎To learn more: Subscribe: https://goo.gl/4vDQzT website: http://statslectures.com Facebook:https://goo.gl/qYQavS Twitter:https://goo.gl/393AQG Instagram: https://goo.gl/fdPiDn Our Team: Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at UBC. Producer: Ladan Hamadani (B.Sc., BA., MPH) These #RTutorial are created by #marinstatslectures to support the statistics course (#SPPH400) at The University of British Columbia(UBC) although we make all videos available to the public for free.
Hypothesis Testing 4: critical values and rejection regions (one sample t test)
 
02:10
Learn about critical values and rejection regions, and how they are used to decide if you should reject or fail to reject a null hypothesis. This video is the fourth in a series that introduce the concepts and principles of hypothesis testing, in the context of a one-sample t-test.
t Distribution and t Scores in R (R Tutorial 3.4)
 
04:19
In this video, you will learn how to calculate probabilities and find quantiles (or critical values) for the student t distribution. We will present the pt, dt and qt commands in R. This video is a tutorial for programming in R Statistical Software for beginners.
Calculate  Odds Ratio and Relative Risk  in R | R Tutorial 4.8 | MarinStatsLectures
 
06:52
Learn how to calculate the relative risk, odds ratio and risk difference (also known as attributable risk) using the epiR package in R. These are numeric summaries for analyzing 2x2 tables, also known as cross-tabluations. This video provides a beginner introduction to programming in R Statistical Software. You can access and download the "LungCapData" dataset here: Excel format: https://bit.ly/LungCapDataxls Tab Delimited Text File: https://bit.ly/LungCapData Here is a quick overview of the topics addressed in this video: 0:00:11 what do "relative risk", "odds ratio" and "attributable risk" measure? 0:00:34 how to produce a 2-way table for two categorical variables in R using the "table" command 0:00:47 how to produce a side by side barplot in R using "barplot" command and "beside" argument 0:01:40 how to load the library for a package installed in R 0:02:04 how to access help for a package installed in R 0:02:19 how to calculate "relative risks", "odds ratios" and "attributable risks" using the "epi.2by2" command 0:02:36 how to specify whether the data is from a cohort study or case-control study using the "cohort.count" or "case.control" arguments 00:02:50 how to set the confidence interval in R using the "conf.level" argument 0:03:18 how to interpret the odds ratio 0:03:44 how to present the data in a table using the standard a,b,c,d notation of exposed/unexposed and diseased/not-diseased using "matrix" command 0:05:12 how to present the data in a table using the standard a,b,c,d notation of exposed/unexposed and diseased/not-diseased using square brackets and "cbind" commands 0:05:44 how to add names to the columns of a table using "colnames" command
Categorical Variables in Linear Regression in R, Example #2 (R Tutorial 5.8)
 
06:31
Learn how to include a categorical variable (a factor or qualitative variable) in a regression model in R. You will also learn how to interpret the model coefficients, and produce a related plot. The video provides a tutorial for programming in R Statistical Software for beginners. You can access and download the "LungCapData" dataset here: Excel format: https://bit.ly/LungCapDataxls Tab Delimited Text File: https://bit.ly/LungCapData Here is a brief overview of the topics addressed in this video:
apply() Function in R (R Tutorial 1.14)
 
06:49
Learn how to use the "apply()" function in R, to apply a function to all rows or columns of a data frame. The apply function essentially is a specialized loop function, although it is more efficient than a simple for-loop. You will also learn the use of the "ColMeans", "ColSums", "RowMeans", and "RowSums" functions. This video is a tutorial for programming in R Statistical Software for Statistics and Data Science beginners, using RStudio. You can access the dataset (Stock Example Data) and R script (Apply Function) here: http://www.statslectures.com/index.php/r-stats-datasets Visit www.statslectures.com for more videos and tutorials on R

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