Multiple Linear Regression Use Dataset IQ 1 Relationship Between Eighth Grade IQ, Eighth Grade Abstract Reasoning and Ninth grade Math Score For a statistics class project, students examined the relationship between x 1 = 8th grade IQ, x2 = 8th grade Abstract Reasoning and y = 9th grade math scores for 20 students. The data are displayed below. Student 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Math Score 33 31 35 38 41 37 37 39 43 40 41 44 40 45 48 45 31 47 43 48 IQ 95 100 100 102 103 105 106 106 106 109 110 110 111 112 112 114 114 115 117 118 Abstract Reas 28 24 29 30 33 32 34 36 38 39 40 43 41 42 46 44 41 47 42 49 Open the dataset IQ found in the Datasets folder in ANGEL. Perform a linear regression with the Response (dependent variable) math score and the variables IQ and Abstract_Reas as the Predictors (independent variables). Store/Save the (unstandardized) Residuals and Fitted(Predicted) values. The output should look as follows: a. What is the regression equation and provide an interpretation of each slope in terms of the change in Y per unit change in X? b. Create two scatter plots of the measurements by selecting math score as the response (y-axis), IQ and abstract reasoning as the predictors (x-axis) Describe the relationship between math score and IQ and math score and abstract reasoning. c. Based on the output, what is the test of the slopes for this regression equation? That is, provide the null and alternative hypotheses, the test statistic, p-value of the test, and state your decision and conclusion. d. From the output, what is the meaning of the ANOVA F-test? Provide the two hypotheses (Ho and Ha) statements, decision and conclusion. e. Check assumptions of constant variance (a scatterplot of the residuals versus the fits(predicted) values) and normality. What are your conclusions based on these graphs? MINITAB: Scatterplot by Graph > Scatter Plot > Simple. Probability plot by Graph > Probability Plot > Single