product will create a demand for it among department store buyers. The following table shows the amount (ten thousand pesos) spent for advertising the fall line of jeans for eight years and the number of pairs of jeans sold (in thousands) in each fall line. Amount Number Year of Jeans spent 50 1985 45 1986 65 60 1987 75 80 1988 100 95

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Author:Amos Gilat
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Chapter1: Starting With Matlab
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3. A jeans manufacturer knows that a large budget for television advertising of his
product will create a demand for it among department store buyers. The following table
shows the amount (ten thousand pesos) spent for advertising the fall line of jeans for
eight years and the number of pairs of jeans sold (in thousands) in each fall line.
Amount
Number
Year
spent
of Jeans
1985
50
45
1986
65
60
1987
75
80
1988
100
95
1989
125
120
1990
140
150
1991
170
145
1992
195
190
Use linear regression to predict the number of pairs of jeans sold, in terms of the amount
spent on the television advertising.
Answer the following:
a. What is the coefficient of correlation?
b. What is the y-intercept and the slope?
c. What is the regression equation?
d. What is the coefficient of determination, r?? Assess the model by interpreting r?.
e. Use the regression equation for description and/or prediction. (If the
manufacturer spends P2M in advertising, what would be his expected sales?)
f. Is there a significant relationship between the variables? Explain your answer.
Transcribed Image Text:3. A jeans manufacturer knows that a large budget for television advertising of his product will create a demand for it among department store buyers. The following table shows the amount (ten thousand pesos) spent for advertising the fall line of jeans for eight years and the number of pairs of jeans sold (in thousands) in each fall line. Amount Number Year spent of Jeans 1985 50 45 1986 65 60 1987 75 80 1988 100 95 1989 125 120 1990 140 150 1991 170 145 1992 195 190 Use linear regression to predict the number of pairs of jeans sold, in terms of the amount spent on the television advertising. Answer the following: a. What is the coefficient of correlation? b. What is the y-intercept and the slope? c. What is the regression equation? d. What is the coefficient of determination, r?? Assess the model by interpreting r?. e. Use the regression equation for description and/or prediction. (If the manufacturer spends P2M in advertising, what would be his expected sales?) f. Is there a significant relationship between the variables? Explain your answer.
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