In: Statistics and Probability
Jorge Jones, a recent management graduate has a new job as a shelf stocker at the local Shop and Stop (bad job market). In order to maintain some of the knowledge he gained in college, Jorge wants to apply regression analysis to predict weekly sales on the cereal aisle.
He believes there would be a relationship between the shelf space that a particular product takes up and the sales of that product. Jorge has gathered the following data:
Shelf Space |
Weekly Sales |
5 |
160 |
16 |
230 |
7 |
220 |
15 |
270 |
6 |
140 |
17 |
280 |
10 |
190 |
21 |
260 |
11 |
240 |
25 |
350 |
14 |
260 |
22 |
310 |
a. Which is the independent/explanatory variable?
b. Which is the dependent/response variable?
Enter the data into an Excel spreadsheet.
c. Create a scatterplot for these data. How would you interpret the scatterplot?
Run a regression analysis using Data Analysis/Regression Tool and use the output to answer the following questions:
d. What is the value of the correlation coefficient? How would you interpret it?
e. What is the value of the coefficient of determination? How would you interpret it?
f. Write the hypotheses for the test of the slope.
g. What is the p-value for the test of the slope? How would you interpret the p-value?
h. What is the regression formula resulting from this analysis between Shelf Space and Weekly Sales?
i. Use the regression formula to estimate the Weekly Sales for a product that has a Shelf space of 23.
j. Use the regression formula to estimate the Weekly Sales for a product that has a Shelf space of 8.