Explanation: Step 1: Compute the values needed for the ANOVA Table Portfolio Advisor (Block) 1 2 7.8 4 13.7 7.6 8.6 14.7 10.8 12.5 4.8 11.8 8.6 2.4 11.3 10.8 5.6 3.8 95 Computations: a=4 b=4 N=ab=16 Portfolio Advisor 1 2 3 7.8 4 Vi- 13.7 8.6 7.6 14.7 10.8 44.8 W N 12.5 4.8 11.8 42.7 8.6 4 11.3 2.4 10.8 35.5 5.6 3.8 9.5 y 1 22.6 21.3 38.7 36.2 46.8 147.4 1443 = y- 409.65 372.34 562.22 TSS = yi - = (147.4 + 409.65 + 372.34 + 562.22) (144.3)2 16 = 1491.61 - 20822.49 16 190.20 SST = Sy b N = [(44.8)3 + (42.7)2 + (35.5)2 + (21.3)2) _ (144.3)# 16 - A 84.66 SSB = La N = [(22.6)2 + (38.7)2 + (36.2)2 + (46.8)2] - (144.3)2 16 - ~ 75.88 SSE = TSS - SST - SSB = 190.20 - 84.66 - 75.88 = 29.66 SST 84.66 MST = a - 1 4-1 28.22 SSB 75.88 MSB = b 25.29ECON7300: Statistical Project Assignment (Part 1]), Semester 2, 2022 Instruction: (A) Questions in this paper should be answered by students whose surnames fall within the range :\\-K. (B): Use the Excel les 'Datasetl part I] to answer questions asked. (C) A heavy penalty will be applied if your answers are not based on datasets assigned lo you. ECON7300: Statistical Project Assignment (Part II), Semester 2, 2022 Instructions for Dataset1 part II: Simple Regression Analysis The cases that make up this dataset are types of cars. For a sample of 223 types of cars sold in Australia during the 2010 and 2011 model years, we have the base price (bprice) and the horsepower (hpower) of the engine. The variables in the dataset are: bprice (Y, in Australian dollars) hpower (X, in units) The dependent variable for your analysis is bprice. Answer the following questions using Datasetl part II. (a) Estimate a regression model using X to predict Y (state the simple linear regression equation). (b) Interpret the meaning of the slope. (c) Predict Y when X = 210 (d) Compute the coefficient of determination and interpret its meaning. (e) Compute the standard error of the estimate and interpret its meaning. Judge the magnitude of the standard error of the estimate. (f) Perform a residual analysis (plot the residuals) and evaluate whether the assumptions of regression have been violated. (g) Test for the slope using t test (follow all the necessary steps). Assume 5% level of significance. (h) Test for the slope using F test (follow all the necessary steps). Assume 5% level of significance. (i) Test for the correlation coefficient (follow all the necessary steps). Assume 5% level of significance. (j) Compute a 95% confidence interval estimate of the mean Y for all types of cars sold in Australia during 2010 and 201 1 model years when X = 210 and interpret its meaning. (k) Compute a 95% prediction interval of Y for a type of car sold during the 2010 and 201 1 model years when X = 210 and interpret its meaning