![]() ![]() Regression analysis is sometimes called 'least squares' analysis because the method of determining which line best 'fits' the data is to minimize the sum of the squared residuals of a line put through the data. The resulting spreadsheet is shown in Figure 5.6. If you have been using Excels own Data Analysis add-in for regression (Analysis Toolpak), this is the time to stop. The regression problem comes down to determining which straight line would best represent the data in Figure 13.8. See Chapter 4.6 for a review of the t-test.Ī third approach to completing a regression analysis is to program a spreadsheet using Excel’s built-in formula for a summationĪnd its ability to parse mathematical equations. ![]() Whereas, when games played or 3 point field goals made increases by 1. Also shown are the 95% confidence intervals for the slope and the y-intercept ( lower 95% and upper 95%). The model has an intercept of 13.8, so when the free throw increases by 1 percent, the salary would increase by 1.4 million. The results of these t-tests provide convincing evidence that the slope is not zero, but there is no evidence that the y-intercept differs significantly from zero.
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