In the Add-Ins available box, select theĪnalysis ToolPak check box, and then click.Click the Microsoft Office Button, and then click.To use it inĮxcel, however, you need to load it first. That is available when you install Microsoft Office or Excel. The Analysis ToolPak is a Microsoft Office Excel add-in program When you load the Analysis Toolpak, the DataĪnalysis command is added to the Tools menu. Installed on your computer, click Yes to install it. Message that tells you the Analysis Toolpak is not Tip If Analysis Toolpak is not listed, click Browse To use the Toolpak in Excel, however, you needĪdd-Ins window, check the Analysis Toolpak box. Instructions for installing Analysis Toolpak on a Mac). Is available when you install Microsoft Office or Excel (See later for The Analysis Toolpak is an Excel add-in program that Which version of Excel do you have installed on your computer? However the Multiple R and R Square are the two most important.Install the Excel Data Analysis Tool Pack Unless you understand statistics and calculating regression models, the values at the bottom of the summary won't have a lot of meaning. Significance F: Statistical value known as P-value of F.This provides the significance of the regression model. F: The F statistic (F-test) for null hypothesis.MS: Mean square of the regression data.The ratio of the residual sum of squares versus the total SS should be smaller if most of your data fits the regression line. df: Statistical value known as degrees of freedom related to the sources of variance.The remaining values in the regression output give you details about smaller components in the regression analysis. Observations: The number of observations in your regression model.If this error is small then your regression results are more accurate. Standard Error: How precise the regression analysis results are.Adjusted R Square: A statistical value called R square that's adjusted for the number of independent variables you've chosen.Statistically, this is the sum of the squared deviations from the mean. R Square: The Coefficient of Determination, which shows how many points between the two variables fall on the regression line.1 indicates a strong correlation between the two variables, while -1 means there's a strong negative relationship. Multiple R: The Correlation Coefficient.
Each of these numbers has the following meanings:
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