Question 17 1 points Save Answer The numbers of copies of a college textbook sold quarterly over the past four years have time series with seasonal pattern, to forecast the quarterly sales of the textbook, the following regression equation was found: \ :lllO , 620 erl , 13:0 9112 + 290 (ms ,where Qtr1, QtrZ , and QtrS are dummy variables corresponding to Quarters 1, 2 and 3. The sales forecast for Quarter 4 of the next year is C? 1320 C7 2120 t) 2214 C 1423 Exhibit 1-1. A multiple linear regression was used to study how family spending (y) is influenced by income (x1), family size (x2), and additions to savings (x3). The variables y, X1, and x3 are measured in thousands of dollars per year. The following results were obtained ANOVA Source of variation DF SS Regression k = 3 SSR = 28 Residual n-k-1 = 26 SSE = 80 Total n-1 = SST = Coefficients Standard Error Intercept 7.58 X1 61 =-2.35 0.6379 x2 62 = 2.5 0.44 x3 63 = 0.35 0.33 Refer to Exhibit 1-1. percent of variations in family spending (y) was explained by the estimated regression model is O 36% O 77% O 26% O 11%Question 21 If the margin of error in an interval estimate of p is 6.6, the interval estimate equals 02:16 0 x i 4.508 Question 22 1 points Save Answer The manager of a grocery store has taken a random sample of 100 customers. The average length of time it took the customers in the sample to check out was 5.5 minutes. The population standard deviation is known to be (16 minute. We want to test to determine whether or not the mean waiting time of all customers is significantly more than 5 minutes The test statistic is C? 3.33 r; 833 f; 533 C) 433 Question 23 1 points Save Answer Copy of The numbers of copies of a college textbook sold quarterly over the past four years have time series with seasonal pattern, to forecast the quarterly sales of the textbook, the following regression equation was found: \ =2120 7 620 erl 7 1520 (3:12 + 290 ers , where Qtr1,Qtr2 , and Qtr3 are dummy variables corresponding to Quarters 1, 2 and 3. The sales forecast for Quarter 2 of the next year is 'C.) 1320 'C.) 2120 O 953 O 800 Bicycling World, a magazine devoted to cycling, reviews hundreds of bicycles throughout the year. Its "Road-Race" category contains reviews of bicycles used by riders primarily interested in racing. One of the most important factors in selecting a bicycle for racing is the weight of the bicycle. The following data show the weight (pounds) and price ($) for ten racing bicycles reviewed by the magazine and you obtained the following Excel results. SUMMARY OUTPUT Regression Statistics Multiple R 0.899 R Square 0.808 Adjusted R Square 0.784 Standard Error 1060.958 Observations 10 ANOVA ss MS F Significance F Regression 37911991 37911991 33.68 0.00040 Residual 9005059 1125632 Total 46917050 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 26786 3679 7.28 8.5E-05 18303 35269 Weight -1321 228 -5.80 0.0004 -1845 -796 The t test to determine whether the price and weight are related is O 2.17 O 0.50 O 7.12 O -5.80Bicycling World, a magazine devoted to cycling, reviews hundreds of bicycles throughout the year. Its "Road-Race" category contains reviews of bicycles used by riders primarily interested in racing. One of the most important factors in selecting a bicycle for racing is the weight of the bicycle. The following data show the weight (pounds) and price ($) for ten racing bicycles reviewed by the magazine and you obtained the following Excel results. SUMMARY OUTPUT Regression Statistics Multiple R 0.899 R Square 0.808 Adjusted R Square 0.784 Standard Error 1060.958 Observations 10 ANOVA SS MS F Significance F Regression 37911991 37911991 33.68 0.00040 Residual 9005059 1125632 Total 46917050 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 26786 3679 7.28 8.5E-05 18303 35269 Weight -1321 228 -5.80 0.0004 -1845 -796 The predicted price of a weigh of 17.8 lb is O -1905 O 3272 O 12000 O 50292Question 28 1 points Save Aasw Exhibit 1-1. Ainultiple linear regression was used to study how family spending (y) is influenced by income (X1 ). family size (X2). and additions to savings {X3}. The variables y. X1. and X3 are measured in thousands of dollars per year. The follmving results were obtained. Snurce of \\ arintmn Regression Residual Tatal Standard Error Refer to Exhibit 171 . 2J7 .358 t 114 4.45 The Value of the t statistic for testing whether Xi and y are related is Bicycling World, a magazine devoted to cycling, reviews hundreds of bicycles throughout the year. Its "Road-Race" category contains reviews of bicycles used by riders primarily interested in racing. One of the most important factors in selecting a bicycle for racing is the weight of the bicycle. The following data show the weight (pounds) and price ($) for ten racing bicycles reviewed by the magazine and you obtained the following Excel results. SUMMARY OUTPUT Regression Statistics Multiple R 0.899 R Square 0.808 Adjusted R Square 0.784 Standard Error 1060.958 Observations 10 ANOVA df SS MS F Significance F Regression 37911991 37911991 33.68 0.00040 Residual 9005059 1125632 Total 46917050 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 26786 3679 7.28 8.5E-05 18303 35269 Weight -1321 228 -5.80 0.0004 -1845 -796 The 95% confidence interval for the slope B1 is O (-1905, -973) O (-1845, -796) O (-1700, -696) O (-1845, -125)