Question

8. (14 marks would work better for stronger students than it would for weaker students. Assume pretest scores measure student "strength"; strong students earn high pretest scores and students earn low pretest scores. The data was analyzed using R. 1+1+1+2+2+2+2+3) The researchers in suspected that active learning model.active-1m (post.active-pre.active) suamary (model.active Coofficients: Estimate Std. Error t value Pr(>ItI) Intercept) 15.14142 2.16061 7.008 1.860-10* pre.active 1.025790.05733 17.8932e-16*** Resicual standard error: 9.355 on 113 degrees of freedom Multiple R-squared: 0.7391, r-statistic: 320.1 on 1 and 113 DF, p-value: 2.20-16 Adjusted R-aquared: 0.7368 Answer the following questions. Put your answers in the chart below. Put only final answers in the chart. Use the space below the chart for rough work. What is the model under consideration? What is the estimated regression line? what is the estimate of σ*the error variance? Look on the R output for the number 7.008. This number is a test statistic. What are the null and alternative hypotheses associated with this test statistic? Give an answer in symbols, not in words Is pretest score a useful predictor of posttest score? To earn any marks, you must justify your answer f. Sam scored 25 on the pretest. What d you predict he would score on the posttest? Present a 95% confidence interval for Use your answer to part e) to make a conclusion regarding the researchers' hypothesis that active learning would work better for stronger student it would for weaker students. Clearly explain your answer s than

Answer 1

A) Post actibe actPve e rost acives4142 1.09579Pre active ave me ''able γ e dictions ypoanesPs is le velot signif, once ond conc 'ude Aras is Ane coelti rient «s 3octive i si