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WCU ECO 252 - ECO 252 Third Exam

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252x0771 11/26/07 (Page layout view!)ECO252 QBA2 Name ______________________ THIRD EXAM Student number_______________ November 29, 2007 Class Day and hour____________ Version 1I. (8 points) Do all the following (2 points each unless noted otherwise). Make Diagrams! Show your work!  14,26~ Nx1.  3820 xP2.  0xP3.  7632 xP4. 075.x 1252x0771 11/26/07 (Page layout view!)II. (22+ points) Do all the following (2 points each unless noted otherwise). Do not answer a question ‘yes’ or ‘no’ without giving reasons. Show your work when appropriate. Use a 5% significance level except where indicated otherwise. Note that this is extremely long and that no one will do all the problems, so look them over!1. Turn in your computer problems 2 and 3 marked as requested in the Take-home. (5 points, 2 point penalty for not doing.)2. In an ordinary 1-way ANOVA, if the computed F statistic is below the value from the F table at the given significance level, we cana. Reject the null hypothesis because the difference between the means is not significantb. Reject the null hypothesis because there is evidence of a significant difference between some ofthe means.c. Not reject the null hypothesis because the difference between the means is not significant.d. Not reject the null hypothesis because the difference between the means is significant.c. Not reject the null hypothesis because the difference between the variances is not significant.d. Not reject the null hypothesis because the difference between the variances is significant.e. None of the above. [7]3. After an analysis if variance, you would use the Tukey-Kramer procedure or similar confidence intervals to check a. For Normalityb. For equality of variancesc. For independence of error termsd. For pairwise differences in meanse. For all of the abovef. For none of the above4. If an ordinary one-way ANOVA has 25 columns 17 rows and  4252517 , the degrees of freedom for the F test are a. 400 and 24b. 408 and 16c. 24 and 400d. 16 and 408e. 400 and 424f. 408 and 424g. 424 and 400h. 424 and 408i. 16 and 24j. None of the above. The correct answer is _______.5. Assuming that your answer to 4 is correct and that the significance level is 5%, the correct value of F from the table is _______. (This may have to be approximate. If so, what did you use?) (1) [12]2252x0771 11/26/07 (Page layout view!)Exhibit 1 A realtor believes that the selling price of a home (in $ thousands) is related to the condition of the home (on a 1 to 10 scale) and the size of the home (in hundreds of square feet). He runs the data belowon Minitab and gets the following.Row Price Size Condition 1 360 23 5 2 200 11 2 3 340 20 9 4 280 17 3 5 280 15 8 6 330 21 4 7 380 24 7 8 250 13 6 MTB > regress c1 2 c2 c3Regression Analysis: Price versus Size, Condition The regression equation isPrice = 64.5 + 11.7 Size + 4.88 ConditionPredictor Coef SE Coef T PConstant 64.539 4.228 15.27 0.000Size 11.7282 0.2317 50.62 0.000Condition 4.8826 0.4494 _____ _____S = 2.75997 R-Sq = 99.9% R-Sq(adj) = 99.8%Analysis of VarianceSource DF SS MS F PRegression 2 25712 12856 1687.70 0.000Residual Error 5 38 8Total 7 25750Source DF Seq SSSize 1 24813Cond 1 899The sum of the price column is 2420 and the sum of the squared numbers in the sales column is not needed.The sum of the 'Size' column is 144 and the sum of the squared numbers in the Size column is 2750.The sum of the ‘Condition’ column is 44 and the sum of the squared numbers in the Condition column is 284.If Price is the dependent variable and Size and Condition are the independent variables we have found that the sum of x1y is 45540 and the sum of x1 x2 is 818. The sum of x2y has not been computed. 6 and 7. In the multiple regression, are the coefficients of size and condition significant at the 5% significance level? Give reasons. Do not do unneeded computations. (2)[15]8. Assuming that the coefficients in the multiple regression are correct, what price would we predict for a home with 20(hundred) square feet and a condition score of 9? (1)9. Using the information in the multiple regression printout, make your result in 8) into a rough prediction interval. (2)10. Using the information in the printout, what is the value of R-squared for a regression of ‘Price’ against‘Size’ alone? (2) [20]3252x0771 11/26/07 (Page layout view!)Exhibit 1 A realtor believes that the selling price of a home (in $ thousands) is related to the condition of the home (on a 1 to 10 scale) and the size of the home (in hundreds of square feet). He runs the data below on Minitab and gets the following.Row Price Size Condition 1 360 23 5 2 200 11 2 3 340 20 9 4 280 17 3 5 280 15 8 6 330 21 4 7 380 24 7 8 250 13 6 MTB > regress c1 2 c2 c3Regression Analysis: Price versus Size, Condition The regression equation isPrice = 64.5 + 11.7 Size + 4.88 ConditionPredictor Coef SE Coef T PConstant 64.539 4.228 15.27 0.000Size 11.7282 0.2317 50.62 0.000Condition 4.8826 0.4494 _____ _____S = 2.75997 R-Sq = 99.9% R-Sq(adj) =99.8%Analysis of VarianceSource DF SS MS F PRegression 2 25712 12856 1687.70 0.000Residual Erro 5 38 8Total 7 25750Source DF Seq SSSize 1 24813Condition 1 899The sum of the price column is 2420 and the sum of the squared numbers in the sales column is not needed.The sum of the 'Size' column is 2750 and the sum of the squared numbers in the Size column is 2950.The sum of the ‘Condition’ column is 44 and the sum of the squared numbers in the Condition column is 284.If Price is the dependent variable and Size and Condition are the independent variables we have found that the sum of x1y is 45540 and thesum of x1 x2 is 818. The sum of x2y has not been computed. 11. Do a simple regression of ‘Price’ against ‘Condition’ alone.a) Compute the sum xy that you will need for this regression. Show your work! (2) Don’t compute stuff that has already been done for you!b) It says that you do not need to know the sum of squares in the sales column. You do however need the spare part 22YnYSSy. Without doing any computing, tell what its value is. (1)c) Compute the coefficients of the equation


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