CAS MA 416 Lecture Notes - Lecture 4: Linear Regression, Null Hypothesis, Decision Rule
8 Nov 2016
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10/6: obtain the correlation r among the 4 variables. The correlation coefficient between x2 and x3 is approximately 0. 01, which indicates there is almost no correlation: problem 6. 10a: fit regression model to the data for three predictor variables. Ha: at least one of b is not 0. Decision rule: reject the null hypothesis if p<0. 05 p<0. 0001<0. 05 therefore, we reject the null hypothesis at 0. 05 significance level. We conclude that at =0. 05 significance level, at lease one independent variable bs is linearly related to y (the total labor hours). It means that 77. 34% of variance in y is explained by the variable xs: obtain the predicted y value for a weekly shipment with x1 = 302,000, x2=7. 20 and x3=0. = 4349. 93+0. 0006*302,000-37. 35*7. 20+621. 53 *0=4262. 21: problem 7. 4a: obtain the analysis of variance table that decomposes the regression sum of squares into extra sums of squares associated with x1; withx3, givenx1;and with x2, givenx1 and. Anova table with decomposition of ssr for three x variables.
