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Basic Excel Business Analytics #48: Data Analysis Regression feature
 
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Download file from “Highline BI 348 Class” section: https://people.highline.edu/mgirvin/excelisfun.htm Learn about how to automatically creates statistics for Linear Regression using the Data Analysis Regression feature. See how to automatically create statistics such as: Correlation, R Squared, Standard Error, Slope, Intercept, SST, SSR, SSE, F Test, Test Statistic, t Test Statistics, p-values, predicted vales, residuals, Residual plots and more. Install: File, Options, Add-ins, Data Analysis Toolpak. Download Excel File Not: After clicking on link, Use Ctrl + F (Find) and search for “Highline BI 348 Class” or for the file name as seen at the beginning of the video.
Views: 23208 ExcelIsFun
Excel - Simple Linear Regression
 
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Simple Linear Regression using Microsoft Excel
Views: 196348 Jalayer Academy
Simple Linear regression analysis using Microsoft Excel's data analysis toolpak and ANOVA Concepts
 
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Knowledge Varsity (www.KnowledgeVarsity.com) is sharing this video with the audience.
Views: 128021 KnowledgeVarsity
Excel 2016 Regression Analysis
 
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Using Data Analysis Toolpak Correlation analysis and interpreting the results
Views: 8448 Tobin Porterfield
Linear Regression in Excel
 
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This video shows you how run a multivariate linear regression in Excel. It also explains some common mistakes people make that results in Excel being unable to perform the regression. It also shows how to enable the Data Analysis Toolpak, although the screen capture software glitched a bit when I recorded this, so I recommend you watch the video entitled "Enabling the Data Analysis Toolpak". Author: David Switzer
Views: 492337 SCSUEcon
Excel Walkthrough 4 - Reading Regression Output
 
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This video uses Anderson 11e Chapter 15 #4 to walk through regression output and explain how to interpret it.
Views: 203603 Jason Delaney
Multiple Linear Regression using Excel Data Analysis Toolpak
 
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LearnAnalytics demonstrates use of Multiple Linear Regression on Excel 2010. (Data Analysis Toolpak). Data set referenced in video can be downloaded at www.learnanalytics.in/blog/wp-content/uploads/2014/02/car_sales.xlsx
Views: 56567 Learn Analytics
Microsoft Excel data analysis tool for statistics mean, median, hypothesis, regression
 
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This video covers a few topics using the data analysis tool. After this video you should be able to: a) Find and use data analysis on excel to calculate statistics b) Calculate the mean, median, mode, standard deviation, range and coefficient variation on a variable set of data in excel. c) Conduct a confidence interval in excel. d) Complete a T-test in excel to help complete a hypothesis test. e) Conduct a linear regression analysis output from excel and create a scatter diagram.
Views: 84885 Me ee
9.2.23 Simple Linear Regression with Residuals - Excel Data Analysis Toolpack
 
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How to find a regression line equation and analyze residuals using Excel's Data Analysis Tool Pack. Larson 9.2.33
Regression output using Data Analysis in Excel
 
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How to install Data Analysis Addin in Excel: https://youtu.be/SqpSwxJ9t2k This video shows how to generate simple linear regression statistics using the Data Analysis Addin in Excel –intercept, slope, regression equation, SSR, SSE, SST, correlation coefficient (r), coefficient of determination (R-square), and standard error of estimate.
Views: 6979 Joshua Emmanuel
Basic Excel Business Analytics #50: Introduction to Multiple Regression, Data Analysis Regression
 
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Download file from “Highline BI 348 Class” section: https://people.highline.edu/mgirvin/excelisfun.htm Learn: 1) (00:13) Estimated Multiple Regression Equation. 2) (00:58) Example 1: Predict Annual Credit Card Charges based on Annual Income (x2) and Number of Years Post High School Eduction (x2) 3) (07:31) Example 2: Predict Risk of Stroke based on Age (x1), Blood Pressure (x2) and Smoking (Categorical Variable) (X3) Download Excel File Not: After clicking on link, Use Ctrl + F (Find) and search for “Highline BI 348 Class” or for the file name as seen at the beginning of the video.
Views: 7104 ExcelIsFun
Conducting a Multiple Regression using Microsoft Excel Data Analysis Tools
 
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This video demonstrates how to conduct and interpret a multiple linear regression (multiple regression) using Microsoft Excel data analysis tools. Multiple regressions return the contribution of multiple predictor variables on one outcome variable. Predicted values for the outcome variable are calculated using the estimated regression equation.
Views: 6309 Todd Grande
How to do Linear Regression with Excel Data Analysis Toolpak
 
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http://alphabench.com/data/linear-regression.html Demonstration of linear regression in Excel using the data analysis toolpak, with a discussion of the output generated from the regression tool. This video was shot in Excel 2007, but the technique is the same for Excel 2008, 2010, 2013 and 2016. All statistics and interpretations are the same regardless of Excel version. It would work for Excel 2011 if Microsoft hadn't removed the Data Analysis Toolpak from that version. By the way, if you are trying to do this in Excel 2011 for MAC OS you can download a free companion software called StatPlusLE. Linear regression is one of the most common statistical techniques in use for making predictions and forecasting behavior. This Tutorial explains the notable statistics and how to use the linear model in making predictions. See our visual take on regression: http://alphabench.com/data/visual-linear-regression.html
Views: 105248 Matt Macarty
Multiple Linear regression analysis using Microsoft Excel's data analysis toolpak and ANOVA Concepts
 
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Learn how to conduct multiple linear regression using Excel data analysis toolpak
Views: 107827 KnowledgeVarsity
Multiple Regression in Excel
 
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Multiple Regression in Excel in a nutshell. Focusing on Excel functionality more than presentation of regression theory.
Views: 49207 Jalayer Academy
OLS Regression in Excel
 
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This is a walk through of estimating an ordinary least squares regression using Excel. I work through all of the calculations and then check the answers using the Data Analysis tool in Excel.
Views: 3044 Shane Van Dalsem
Multiple Regression Interpretation in Excel
 
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This video provides an example of interpreting multiple regression output in excel. The data set comes from Andy Field's "Discovering Statistics Using SPSS" (2009, 3rd Edition).
Views: 308306 TheWoundedDoctor
Basic Excel Business Analytics #56: Forecasting with Linear Regression: Trend & Seasonal Pattern
 
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Download file from “Highline BI 348 Class” section: https://people.highline.edu/mgirvin/excelisfun.htm Learn: 1) (00:11) Forecasting using Regression when we see a trend and belief the trend will extend into the future. Will will predict outside the Experimental Region with the Assumption is that trend continues into future. 2) (00:53) Forecast a Trend using Simple Liner Regression. We use the Data Analysis Regression Feature. 3) (03:22) Learn how to use FORECAST function. 4) (08:57) Forecast a Seasonal Pattern using Multiple Regression and three Categorical Variables for quarter using Multiple Linear Regression. We use the Data Analysis Regression Feature. 5) (12:12) VLOOKUP & MATCH functions with Mixed Cell References to populate new categorical variable columns with the Boolean ones and zeroes. 6) (19:53) Forecast a Trend with a Seasonal Pattern using Multiple Regression and three Categorical Variables for quarter and one quantitative variable using Multiple Linear Regression. We use the Data Analysis Regression Feature. 7) Download Excel File Not: After clicking on link, Use Ctrl + F (Find) and search for “Highline BI 348 Class” or for the file name as seen at the beginning of the video.
Views: 57040 ExcelIsFun
Excel Regression Analysis Output Explained
 
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Overview of the Excel regression analysis output. For more detail, go to: http://www.statisticshowto.com/excel-regression-analysis-output-explained/
Views: 56559 Stephanie Glen
Logistic Regression Using Excel
 
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Predict who survives the Titanic disaster using Excel. Logistic regression allows us to predict a categorical outcome using categorical and numeric data. For example, we might want to decide which college alumni will agree to make a donation based on their age, gender, graduation date, and prior history of donating. Or we might want to predict whether or not a loan will default based on credit score, purpose of the loan, geographic location, marital status, and income. Logistic regression will allow us to use the information we have to predict the likelihood of the event we're interested in. Linear Regression helps us answer the question, "What value should we expect?" while logistic regression tells us "How likely is it?" Given a set of inputs, a logistic regression equation will return a value between 0 and 1, representing the probability that the event will occur. Based on that probability, we might then choose to either take or not take a particular action. For example, we might decide that if the likelihood that an alumni will donate is below 5%, then we're not going to ask them for a donation. Or if the probability of default on a loan is above 20%, then we might refuse to issue a loan or offer it at a higher interest rate. How we choose the cutoff depends on a cost-benefit analysis. For example, even if there is only a 10% chance of an alumni donating, but the call only takes two minutes and the average donation is 100 dollars, it is probably worthwhile to call.
Views: 155860 Data Analysis Videos
Regression in Excel | Simple Linear Regression | Data Science on Excel
 
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In this video you will learn how to perform Simple Linear Regression in Excel. For all our videos & Study packs visit: http://analyticuniversity.com/
Views: 4283 Analytics University
How to perform a Regression Analysis on Microsoft Excel 2016 on a Mac
 
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This video is about RegressionAnalysis
Views: 69360 David Orndorff
How To... Perform Simple Linear Regression in Excel 2010
 
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Use Excel to generate a Simple Regression Equation and to add a line of best fit to compare two sets of data. Excel also gives you an R-squared value to show how strong the correlation is between the two sets of data.
Views: 164367 Eugene O'Loughlin
Correlation and Regression with Excel
 
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This demonstration shows you how to get a correlation coefficient, create a scatterplot, insert the regression line, and get the regression equation for two variables. This demonstration corresponds to the Introduction to Statistics, Think & Do textbook, by Scott Stevens (http://www.StevensStats.com).
Views: 55691 Scott Stevens
Excel 10 (Problem 16) Experimental data analysis, curve fitting, linear regression, trendline.
 
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Experimental data analysis, curve fitting, linear regression, trendline. Lone Star College CyFair ENGR 2304 Programming for Engineers Example Problems: Excel Problem 16.
Views: 2101 Yiheng Wang
Excel - Quick Intro to Scatterplots, Bivariate Data, and Regression
 
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Scatterplots, Bivariate Data, and Regression
Views: 6064 Jalayer Academy
Basic Excel Business Analytics #51: Testing Significance of Regression Relationship with p-value
 
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Download file from “Highline BI 348 Class” section: https://people.highline.edu/mgirvin/excelisfun.htm Learn How to do Hypothesis Testing to Test the significance to a linear relationship using the Data Analysis Regression feature. Download Excel File Not: After clicking on link, Use Ctrl + F (Find) and search for “Highline BI 348 Class” or for the file name as seen at the beginning of the video.
Views: 12538 ExcelIsFun
Prediction in Simple Regression
 
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Using some made up ice cream sales vs. temperature data, I demonstrate how to calculate and interpret a point prediction and 90% prediction interval using MS Excel 2007
Views: 70018 ProfTDub
Nonlinear Regression in Microsoft Excel
 
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A three parameter (a,b,c) model y = a + b/x + c ln(x) is fit to a set of data with the Excel solver add-in. This tutorial walks through the process of installing the solver, setting up the objective (normalized sum of squared errors), and adjusting the parameter values to minimize the SSE.
Views: 117716 APMonitor.com
Multiple Regression - Dummy variables and interactions - example in Excel
 
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In this video, I present an example of a multiple regression analysis of website visit duration data using both quantitative and qualitative variables. Variables used include gender, browser, mobile/non-mobile, and years of education. Gender and mobile each require a single dummy variable, while browser requires several dummy variables. I also present models that include interactions between the dummy variables and years of education to analyze intercept effects, slope effects, and fully interacted models. In short, I cover: - multiple category qualitative variables - dummy variables - intercept effects - slope effects - dummy interactions I hope you find it useful! Please let me know if you have any questions! --Dr. D.
Views: 225291 Jason Delaney
Multiple Regression with Categorical Variable
 
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If you found this useful, look for my ebook on Amazon, Straightforward Statistics using Excel and Tableau.
Views: 50406 Stephen Peplow
stock returns regression in excel
 
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Download excel file to go with video: http://www.codible.com/pages/84 Analyze stock price data using Microsoft Excel to plot returns, and plot a regression line between the stock returns. Some good books on Excel and Finance: Financial Modeling - by Benninga: http://amzn.to/2tByGQ2 Principles of Finance with Excel - by Benninga: http://amzn.to/2uaCyo6
Views: 69272 Codible
Multiple Regression Explained with Excel
 
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This tutorial covers the basic concepts of Multiple Regression. Before watching this tutorial please make sure you are familiar with the basic concepts of simple linear regression, if you need a review, go to https://youtu.be/BLRjywb0mes. In this tutorial we discuss introduce the multiple regression model and discuss what its parameters mean and how to test the significance of the slopes of each independent variable using a t test. This tutorial also shows how to conduct regression analysis using Excel, and the output for multiple regression hypothesis tests for individual slopes is examined using the t tests statistic and the p value approach. The significance of r and the adjusted r squared values is also discussed. The ANOVA table and F test are not covered in this tutorial.
Views: 36458 Learn Something
Regression in Excel using the Data Analysis Toolpak add-in
 
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Excel isn't brilliant at running statistical tests, but the Data Analysis Toolpak add-in does make it a bit easier. If you don't have this add-in you'll need to add it in first.
Views: 2528 BrunelASK
Nonlinear Regression Using Excel
 
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Nonlinear Regression Using Excel
Views: 35773 Sam Hijazi
How to Perform a Linear or Multiple Regression (Excel 2013)
 
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Performing a regression is a useful tool in identifying the correlation between variables. This video gives step-by-step instructions in how to perform one in Excel 2013. For more detailed write ups on similar topics, head over to my website at http://www.economistician.com Connect with me on social media for more! LinkedIn: http://linkedin.economistician.com Twitter: http://twitter.economistician.com =============== Source Files =============== DIESEL (measured in $ per gallon) http://www.eia.gov/dnav/pet/hist_xls/EMD_EPD2D_PTE_NUS_DPGm.xls OIL (measured in $ per barrel) http://www.eia.gov/dnav/pet/hist_xls/RWTCm.xls RGDP (measured in $ billions) http://www.macroadvisers.com/assets/MA-Monthly-GDP-Index28.xlsx
Views: 19801 economistician.com
3 ways how to perform multiple regression in excel. Linest(), data analysis and matrix calculations.
 
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How to perfrom multiple linear regression. Three ways. First - linest() - using excel formula, second - using "regression" in data analysis toolpack , third ( 03:06 ) - using linear matrix algebra. I hope this will give some insight on how to deal with matrices in excel. Hyperlink mentioned in video - http://www.mathsisfun.com/algebra/matrix-inverse.html
Views: 6992 Didzis Lauva
Explanation of Regression Analysis Results
 
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A brief explanation of the output of regression analysis. For more information visit www.calgarybusinessblog.com
Views: 427804 Matt Kermode
How To Calculate Beta on Excel - Linear Regression & Slope Tool
 
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Learn how to calculate Beta on Microsoft Excel with this step-by-step tutorial! This simple, yet easy to understand video provides you with the ability to calculate the beta of any company’s stock price. Beta is typically used by investors to evaluate the risk of investing into a certain stock. Many financial institutions provide a list of company’s beta, but they can sometimes be inaccurate. Calculating Beta on your own is the only way to be sure you are receiving the correct information. The worst part about using a pre-calculated beta provided by someone else is that you are unaware of the time period that was taken into consideration when calculating that beta. By calculating it yourself you will know the exact span of time that your beta includes and you will have much more flexibility when calculating the desired time span. Send me something! (Letters are more fun than emails!) PO Box 7329 NEW YORK, NY 10116
Views: 18430 Nate O'Brien
Excel Regression Output - How You Can Quickly Read and Understand It
 
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How to quickly read and understand the important parts of the output of a Regression done in Excel. You be able to immediately recognize and understand the four most important parts of the output of an Excel Regression. Become an Excel Statistical Master !
Views: 218817 excelmasterseries
Linear Regression in Excel
 
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Using Excel to create a scatter plot, calculate and graph a trendline.
Views: 838731 lbcccampbem
Simple Regression Basics
 
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A simple regression analysis is done using made up data of ice cream sales related to high temperature for a period of twenty days. A fitted line plot is first constructed, the slope and intercept are interpreted, then I run a regression, clean up the output, and interpret a few more regression statistics.
Views: 311367 ProfTDub
Residual Analysis of Simple Regression
 
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I take the ice cream sales vs. temp data, run a regression, and produce residual (and fitted values and standardized residuals output) and two residuals plots - to check the assumptions of independence and constant variance. Since the data is a time-series, one of the plots produced is residuals vs. time to check if independence over time is satisfied.
Views: 76512 ProfTDub
regression on excel 2011
 
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A brief instructional video on using Excel for Mac 2011 as a tool for linear regression.
Views: 67372 David Eckstrom
Regression analysis in excel
 
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Creating regression output in excel
Views: 15658 ProfLMurray
Marketing Statistics in Excel 9.1 Regression Analysis, Univariate and Multivariate Regression
 
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Learn about managing data in Excel. These are the Video supplements for Workbook of Quantitative Tools and Techniques in Marketing, 2nd Ed. Part of a full MOOC.
Views: 3457 Tim J Smith PhD
Quadratic Regression Analysis in Excel
 
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Step by step instructions on how to do a quadratic (2nd-order) regression analysis (least-squares curve fit) using Microsoft Excel, and then how to plot the results.
Views: 37480 John Cimbala
Multiple Regression in Excel - P-Value; R-Square; Beta Weight; ANOVA table (Part 1 of 3)
 
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Check out our new Excel Data Analysis text: https://www.amazon.com/dp/B076FNTZCV This video illustrates how to perform a multiple regression statistical analysis in Microsoft Excel using the Data Analysis ToolPak. Multiple regression in Excel Regression Analysis Statistical Analysis in Excel Video Transcript: In this video we'll take a look at how to run a multiple regression analysis in Microsoft Excel. Now in this example, notice that we have four variables: college GPA, and that's the GPA after the first year in college, and then we have SAT score, which was taken in high school, and we have social support, and this was a measure of how supported people feel, to what degree they can turn to others for support, and this was also assessed in college, and then we have gender, where we have 1s and 2s, where 1s are males and 2s are females. So in this example, we have a total of four variables and we have 30 rows of data here. And in regression, each row corresponds, most typically, to a different person. So, for example, the first person had a GPA of 3.45 after their first year in college, they had a 1200 on the SAT, a 62 on social support, and they were male, they had a 1 on gender. Now in multiple regression, we have two different kinds of variables, we have the criterion variable, which is also known as the dependent variable, and in this example the criterion variable is college GPA. And then we have predictor variables, and those are also known as independent variables. Here we have 3: SAT score, social support, and gender. And, in multiple regression, we are always going to have at least two predictor variables, or independent variables, and only one criterion variable, or dependent variable. So it's important to get used to this terminology when you're using multiple regression as it can get a little confusing otherwise. So, once again, college GPA is our criterion variable, or our dependent variable, and these three variables are our predictors, or our independent variables. And what we're trying to do in multiple regression is we're trying to use these predictors, SAT score, social support, and gender, to predict our criterion variable, college GPA. And that's at the end of the first year in college once again. And there's one other thing I do want to note here, I have a dichotomous variable here, gender. Of course for gender, there's two values males and females. And that's fine, if I have a dichotomous variable, I can go ahead and enter that into regression as normal. But if I have a categorical variable that has more than two categories, like say ethnicity, let's say we had four categories in ethnicity, I can't just go ahead and enter that as a normal predictor, but instead I have to recode that where I have to have as many predictors for ethnicity as are equal to the number categories minus one. So if I have, for example, four categories of ethnicity, I would need to create three predictors for ethnicity alone so they would be ethnicity 1, ethnicity 2, ethnicity 3, just for that variable. And how to do that is beyond the scope of this video, but it is important to be aware of. So if you do have a categorical variable that has more than two categories you don't want to just go ahead and enter it into the normal multiple regression commands as we're going to do here in Excel. It needs to be re-expressed. But we're good to go with gender, because there's just two categories, or in other words it's dichotomous. OK so let's go ahead and get started. To run the multiple regression in Microsoft Excel, we want to go to Data and then select Data Analysis. And then the Data Analysis window opens. We want to go ahead and scroll down to find Regression. Select that and then click OK. Now here for Input Y range, Y corresponds to our criterion variable, and X corresponds to our predictors. So let's go ahead and start with our Y, since the cursor's flashing in that box. Go ahead and select college GPA and scroll all the way down to select all the values. Then we see B1 through B31 in that box. That looks good. Go ahead and make sure now that you click on the Input X range box, so that it's active. And then now we'll select our three variables and all the values for SAT score, social support, and gender. OK that looks good. So now I have C1 through E31, that's perfect. Next, notice that I did select my labels which I wanted to do. I have the variable names there. So I'm going to go ahead and click on Labels. OK and everything else looks good, so go ahead and click OK. And then here we get our output and it's a little bit compressed so let's go ahead and modify this. First, let's go and change the font to 13 point. And then I'm going to go ahead and expand this by double- clicking on these columns here; that looks good. YouTube Channel (Quantitative Specialists): https://www.youtube.com/user/statisticsinstructor Subscribe today!