Question

A regression model relating units sold (Y), price (X1), and whether or not promotion was used...

A regression model relating units sold (Y), price (X1), and whether or not promotion was used (X2=1 if promotion was used and 0 if it was not ) resulted in the following model. Yhat=120-0.03X1+0.7X2 and the following information is provided. n=15 Sb1=.01 Sb2=0.1

a) Is a price significant variable?

b) Is promotion significant?

Homework Answers

Answer #1

(A) test statistic for price = b1/Sb1

setting b1= -0.03 and Sb1 = 0.01

we get

test statistic t = -0.03/0.01 = -3

degree of freedom = n-2

= 15-2

= 13

Using t distribution table with test statistic (-3) and df(13) w

we get

p value = 0.0102

So, at 0.05 significance level, p value is significant because it is less than significance level of 0.05

Therefore, price is a significant variable at 0.05 significance level

(B)

test statistic for promotion = b2/Sb2

setting b2= 0.7 and Sb2 = 0.1

we get

test statistic t = 0.7/0.1 = 7

degree of freedom = n-2

= 15-2

= 13

Using t distribution table with test statistic (7) and df(13) w

we get

p value = 0.0000

So, at 0.05 significance level, p value is significant because it is less than significance level of 0.05

Therefore, promotion is a significant variable at 0.05 significance level

Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
Exhibit 16-7 When a regression model was developed relating sales (Y) of a company to its...
Exhibit 16-7 When a regression model was developed relating sales (Y) of a company to its product's price (X1), the SSE was determined to be 495. A second regression model relating sales (Y) to product's price (X1) and competitor's product price (X2) resulted in an SSE of 396. The sample size for both models was 33. Refer to Exhibit 16-7. The p-value for testing which model has significantly lower SSE is: Group of answer choices between 0.05 and 0.10 between...
A regression model between sales (y in $1000), unit price (x1 in dollars), and television advertisement...
A regression model between sales (y in $1000), unit price (x1 in dollars), and television advertisement (x2 in dollars) resulted in the following function: ŷ = 7 - 3x1 + 5x2 ​​For this model, SSR = 3500, SSE = 1500, and the sample size is 18. The adjusted R-squared or adjusted coefficient of determination for this problem is 0.7 0.66 0.825 -0.66
A regression model between sales (y in $1000), unit price (x1 in dollars), and television advertisement...
A regression model between sales (y in $1000), unit price (x1 in dollars), and television advertisement (x2 in dollars) resulted in the following function: ŷ = 7 - 3x1 + 5x2 ​​For this model, SSR = 3500, SSE = 1500, and the sample size is 18. The adjusted R-squared or adjusted coefficient of determination for this problem is 0.7 0.66 0.825 -0.66
The following estimated regression model was developed relating yearly income (y in $1000s) of 30 individuals...
The following estimated regression model was developed relating yearly income (y in $1000s) of 30 individuals with their age (x1) and their gender (x2) (0 if male and 1 if female). ŷ = 30 + 0.7x1 + 3x2 Also provided are SST = 1200 and SSE = 384. The estimated income of a 30-year-old male is _____. a. $51 b. $510 c. $5100 d. $51,000
The estimated regression equation for a model involving two independent variables and 55 observations is: y-hat...
The estimated regression equation for a model involving two independent variables and 55 observations is: y-hat = 55.17 + 1.1X1 - 0.153X2 Other statistics produced for analysis include: SSR = 12370.8 SST = 35963.0 Sb1 = 0.33 Sb2 = 0.20 Interpret b1 and b2 in this estimated regression equation b. Predict y when X1 = 55 and X2 = 70. Compute R-square and Adjusted R-Square. e. Compute MSR and MSE. f. Compute F and use it to test whether the...
6. The following estimated regression model was developed relating yearly income (Y in $1,000s) of 30...
6. The following estimated regression model was developed relating yearly income (Y in $1,000s) of 30 individuals with their age (X1) and their gender (X2) (0 if male and 1 if female). ˆ Y =20+0.7X1 +2X2 SST = 1,000 and SSE = 256 b) Is there a significant relationship between the yearly income and the set of predictors (i.e., age and gender)? Use α=0.05 and make sure to show all your steps.
Consider the following data for a dependent variable y and two independent variables,  x1 and x2. x1...
Consider the following data for a dependent variable y and two independent variables,  x1 and x2. x1 x2 y 30 12 94 47 10 108 25 17 112 51 16 178 40 5 94 51 19 175 74 7 170 36 12 117 59 13 142 76 16 211 The estimated regression equation for these data isŷ = −18.37 + 2.01x1 + 4.74x2. Here, SST = 15,182.9, SSR = 14,052.2, sb1 = 0.2471,  and  sb2 = 0.9484. (A) Test for a significant relationship...
A microcomputer manufacturer has developed a regression model relating his sales (Y in $10,000s) with three...
A microcomputer manufacturer has developed a regression model relating his sales (Y in $10,000s) with three independent variables. The three independent variables are price per unit (Price in $100s), advertising (ADV in $1,000s) and the number of product lines (Lines). Part of the regression results is shown below. Coefficient Standard Error Intercept 1.0211 22.8752 Price (X1) -.1523 -.1411 ADV (X2) .8849 .2886 Lines(X3) -.1463 1.5340 Source D.F. S.S. Regression 3 2708.651 Error 14 2840.51 Total 17 5549.12 (a) What has...
A linear regression of a variable Y against the explanatory variables X1 and X2 produced the...
A linear regression of a variable Y against the explanatory variables X1 and X2 produced the following estimation model: Y = 1615.495 + 9.957 X1 + 0.081 X2 + e (527.96) (6.32) (0.024) The number in parentheses are the standard errors of each coefficients i. State the null and alternative hypothesis for the coefficients Select the appropriate test, compute the test statistic based on the information above, and test the null hypothesis for each coefficient by using a level of...
6.    Consider the following sample regression results:             Y hat = 15.4 +    2.20 X1   +...
6.    Consider the following sample regression results:             Y hat = 15.4 +    2.20 X1   + 48.14 X2                 R2 = .355                      (6.14)     (.42)          (5.21)            n = 27 The numbers in the parentheses are the estimated standard errors of the sample regression coefficients. 6. (continued) a.    Construct a 95% confidence interval for b1. b.    Is there evidence of a linear relationship between X2   and Y at the 5% level of significance? c.    If you were to use a global test...
ADVERTISEMENT
Need Online Homework Help?

Get Answers For Free
Most questions answered within 1 hours.

Ask a Question
ADVERTISEMENT