However the Multiple R and R Square are the two most important.Today we are going to show you how to turn on the statistical analysis add-in in MS Excel.Įxcel is excellent when it comes to financial analysis, creating reports, and performing calculations.
Unless you understand statistics and calculating regression models, the values at the bottom of the summary won't have a lot of meaning.
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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