qmst notes8 - The F statistic and its corresponding p-value...

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The F statistic and its corresponding p-value can let us know how well this combination of predictors predicts y. The t statistics and their corresponding p-values can let us know how well each predictor predicts y . R 2 tells us how much of the variation in y is explained by variation in the x scores Residuals -Useful to determine how well the model 'fits'. The difference between the y value and the predicted y value (error): y-ŷ . Calculate the residuals by predicting y for the actual y values we used in the regression analysis. Then, look to see how well the model predicted the actual data. Multiple Regression Output - Seven things to look for: 1)The equation of the regression model; 2)The ANOVA table with the F value for the overall test of the model; 3)The t-ratios, which test the significance of the regression coefficients; 4)The value of SSE-sum of squares of error. Found under ANOVA section of regression table (The sum of all the residuals equal zero); 5)The value of s e ; 6)The value of R
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This note was uploaded on 01/26/2012 for the course QMST 2333 taught by Professor Mendez during the Spring '08 term at Texas State.

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