Homework Answers
a)
y=23+12*15+8*11=291 (Or try this answer also 291000)
Sales can be expected to increase by $12 ..................... expected to increase by $ 8
.
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A shoe store developed the following estimated regression equation relating sales to inventory investment and advertising...
A shoe store developed the following estimated regression equation relating sales to inventory investment and advertisi...
A shoe store developed the following estimated regression equation relating sales to inventory investment and advertising expenditures y = 35+12r16x2 where =inventory investment ($1000s) 1 x2 = advertising expenditures ($1000s) sales ($1000s) a. Predict the sales resulting from a $15,000 investment in inventory and an advertising budget of $10,000. $ b. Interpret bi and b2 in this estimated regression equation. bi Sales can be expected to-Select your answer by $12 for every dollar increase in Select your answer is held...
eBook A shoe store developed the following estimated regression equation relating sales to inventory investment and...
eBook A shoe store developed the following estimated regression equation relating sales to inventory investment and advertising expenditures. y = 35 + 9.21 + 7x2 where 21 = inventory investment ($1000s) 12 = advertising expenditures ($1000s) y = sales ($1000s) a. Predict the sales resulting from a $15,000 investment in inventory and an advertising budget of $10,000. b. Interpret bi and b2 in this estimated regression equation. - Select your answer - ] by $9 for every dollar increase in...
A shoe store developed the following estimated regression equation relating sales to inventory investment and advertising...
A shoe store developed the following estimated regression equation relating sales to inventory investment and advertising expenditures where 1inventory investment ($1000s) = advertising expenditures ($1000s) y sales ($1000s) The data used to develop the model came from a survey of 10 stores; for those data, SST 16,000 and SSR a. Compute SSE, MSE, and MSR (to 2 decimals, if necessary) 12,000 SSE MSE MSR b. Use an F test and α .05 level of significance to determine whether there is...
The following estimated regression equation relating sales to inventory investment and advertising expenditures was given. ý...
The following estimated regression equation relating sales to inventory investment and advertising expenditures was given. ý = 24 + 14x + 7x2 The data used to develop the model came from a survey of 10 stores; for those data, SST = 18,000 and SSR = 12,780. (a) For the estimated regression equation given, compute RS R2 = (b) Compute R, (Round your answer to two decimal places.) (c) Does the model appear to explain a large amount of variability in...
The following estimated regression equation based on 30 observations was presented. ŷ = 17.6 + 3.8x1...
The following estimated regression equation based on 30 observations was presented. ŷ = 17.6 + 3.8x1 − 2.3x2 + 7.6x3 + 2.7x4 The values of SST and SSR are 1,807 and 1,758, respectively. (a) Compute R2. (Round your answer to three decimal places.) R2 = (b) Compute Ra2. (Round your answer to three decimal places.) Ra2 = part 2: the following estimated regression equation relating sales to inventory investment and advertising expenditures was given. ŷ = 27 + 15x1 +...
12.3 A statistical program is recommended. The owner of Showtime Movie Theaters, Inc., would like to...
12.3
A statistical program is recommended. The owner of Showtime Movie Theaters, Inc., would like to predict weekly gross revenue as a function of advertising expenditures. Historical data for a sample of eight weeks follow Develop an estimated regression equation with the amount of television advertising as the independent variable. (Round your numerical values to two decimal places. Let x, represent the amount of television advertising in $1,000s and y represent the weekly gross revenue in $1,000s.) Develop an estimated...
The owner ot Showtime Movie Theaters, Inc., would ike to prodict wecey grosa revenue as a functio...
The owner ot Showtime Movie Theaters, Inc., would ike to prodict wecey grosa revenue as a function of advertising expenditures. Historical data for a sample of cight weeks tollow. Weekly Television Newspaper Advertising Advertising ($1,000s)(1,000s) (1,000s) 5.0 2.0 96 1.5 2.0 1.5 90 3.5 2.5 3.0 94 (a) Develop an etimated regression equation with the amount of television adwartising as the indapendent variable. (Round your numerical values to two decimal places. Lot x represent the amount of television advertising in...
In a regression analysis involving 10 observations, the following estimated regression equation was obtained - 17.9...
In a regression analysis involving 10 observations, the following estimated regression equation was obtained - 17.9 3 .2, -2.5x2 + 7.847 + 2.8x4 (a) Interpret b, in this estimated regression equation. 3.2 is an estimate of the change in y corresponding to a 1 unit change in x, when X, and - -2.5 is an estimate of the change in y corresponding to a 1 unit change in x, when y, y, and constant are held constant are held 2.8...
In a regression analysis involving 36 observations, the following estimated regression equation was developed. û =...
In a regression analysis involving 36 observations, the following estimated regression equation was developed. û = 10 - 5X1 + 4X2 +8.6X3 Also, the following standard errors and the sum of squares were obtained. Sb1 = 4 Sb2 = 2 Sb3 = 7 SST = 4,800 SSE = 1,296 When we increase X1 by 2 units and hold other things constant, Y on average will increase by 36 units U None of the rest increase by 5 units decrease by...
The admissions officer for Clearwater College developed the following estimated regression equation relating the final...
The admissions officer for Clearwater College developed the following estimated regression equation relating the final college GPA to the student's SAT mathematics score and high-school GPA. y = -1.4053 +.0235.21 +.0049.22 where 41 = high-school grade point average C2 = SAT mathematics score y = final college grade point average Round your answers to 4 decimal places. a. Complete the missing entries in this Excel Regression tool output. Enter negative values as negative numbers. I JANOVA Tdf TSS TMSF Regression...
A shoe store developed the following estimated regression equation relating sales to inventory investment and advertising expenditures y = 35+12r16x2 where =inventory investment ($1000s) 1 x2 = advertising expenditures ($1000s) sales ($1000s) a. Predict the sales resulting from a $15,000 investment in inventory and an advertising budget of $10,000. $ b. Interpret bi and b2 in this estimated regression equation. bi Sales can be expected to-Select your answer by $12 for every dollar increase in Select your answer is held...
eBook A shoe store developed the following estimated regression equation relating sales to inventory investment and advertising expenditures. y = 35 + 9.21 + 7x2 where 21 = inventory investment ($1000s) 12 = advertising expenditures ($1000s) y = sales ($1000s) a. Predict the sales resulting from a $15,000 investment in inventory and an advertising budget of $10,000. b. Interpret bi and b2 in this estimated regression equation. - Select your answer - ] by $9 for every dollar increase in...
A shoe store developed the following estimated regression equation relating sales to inventory investment and advertising expenditures where 1inventory investment ($1000s) = advertising expenditures ($1000s) y sales ($1000s) The data used to develop the model came from a survey of 10 stores; for those data, SST 16,000 and SSR a. Compute SSE, MSE, and MSR (to 2 decimals, if necessary) 12,000 SSE MSE MSR b. Use an F test and α .05 level of significance to determine whether there is...
The following estimated regression equation relating sales to inventory investment and advertising expenditures was given. ý = 24 + 14x + 7x2 The data used to develop the model came from a survey of 10 stores; for those data, SST = 18,000 and SSR = 12,780. (a) For the estimated regression equation given, compute RS R2 = (b) Compute R, (Round your answer to two decimal places.) (c) Does the model appear to explain a large amount of variability in...
12.3
A statistical program is recommended. The owner of Showtime Movie Theaters, Inc., would like to predict weekly gross revenue as a function of advertising expenditures. Historical data for a sample of eight weeks follow Develop an estimated regression equation with the amount of television advertising as the independent variable. (Round your numerical values to two decimal places. Let x, represent the amount of television advertising in $1,000s and y represent the weekly gross revenue in $1,000s.) Develop an estimated...
The owner ot Showtime Movie Theaters, Inc., would ike to prodict wecey grosa revenue as a function of advertising expenditures. Historical data for a sample of cight weeks tollow. Weekly Television Newspaper Advertising Advertising ($1,000s)(1,000s) (1,000s) 5.0 2.0 96 1.5 2.0 1.5 90 3.5 2.5 3.0 94 (a) Develop an etimated regression equation with the amount of television adwartising as the indapendent variable. (Round your numerical values to two decimal places. Lot x represent the amount of television advertising in...
In a regression analysis involving 10 observations, the following estimated regression equation was obtained - 17.9 3 .2, -2.5x2 + 7.847 + 2.8x4 (a) Interpret b, in this estimated regression equation. 3.2 is an estimate of the change in y corresponding to a 1 unit change in x, when X, and - -2.5 is an estimate of the change in y corresponding to a 1 unit change in x, when y, y, and constant are held constant are held 2.8...
In a regression analysis involving 36 observations, the following estimated regression equation was developed. û = 10 - 5X1 + 4X2 +8.6X3 Also, the following standard errors and the sum of squares were obtained. Sb1 = 4 Sb2 = 2 Sb3 = 7 SST = 4,800 SSE = 1,296 When we increase X1 by 2 units and hold other things constant, Y on average will increase by 36 units U None of the rest increase by 5 units decrease by...
The admissions officer for Clearwater College developed the following estimated regression equation relating the final college GPA to the student's SAT mathematics score and high-school GPA. y = -1.4053 +.0235.21 +.0049.22 where 41 = high-school grade point average C2 = SAT mathematics score y = final college grade point average Round your answers to 4 decimal places. a. Complete the missing entries in this Excel Regression tool output. Enter negative values as negative numbers. I JANOVA Tdf TSS TMSF Regression...
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