Essay
A company that makes baseball caps would like to predict the sales of its main product, standard little league caps. The company has gathered data on monthly sales of caps at all of its retail stores, along with information related to the average retail price, which varies by location. Below you will find regression output comparing these two variables.
-(A) Estimate the regression model. How well does this model fit the given data?
(B) Is there a linear relationship between X and Y at the 5% significance level? Explain how you arrived at your answer.
(C) Use the estimated regression model to predict the number of caps that will be sold during the next month if the average selling price is $10.
(D) Find a 95% prediction interval for the number of caps determined in (C). Use t- multiple = 2.
(E) Find a 95% confidence interval for the average number of caps sold given an average selling price of $10. Use a t-multiple = 2.
(F) How do you explain the differences between the widths of the intervals in (D) and (E)?
Correct Answer:

Verified
(A)
= 147984.44 + -7370.94
; since
...View Answer
Unlock this answer now
Get Access to more Verified Answers free of charge
Correct Answer:
Verified
(A)
View Answer
Unlock this answer now
Get Access to more Verified Answers free of charge
Q2: In order to test the significance of
Q3: Heteroscedasticity means that the variability of Y
Q31: The term autocorrelation refers to the observation
Q63: In order to estimate with 90% confidence
Q72: A point that "tilts" the regression line
Q73: In a simple linear regression problem, if
Q74: A manufacturing firm wants to determine whether
Q76: Time series data often exhibits which of
Q78: In multiple regression with k explanatory variables,
Q82: The t-value for testing <img src="https://d2lvgg3v3hfg70.cloudfront.net/TB1387/.jpg" alt="The