Home » Business forecasting with multiple regression models w excel serious

Business forecasting with multiple regression models w excel serious

Estimate values for b0, b1, and b2 for the following model:


b. Are the signs you find for the coefficients consistent with your expectations? Explain.


c. Are the coefficients for the two explanatory variables significantly different from zero? Explain.


d. What percentage of the variation in AS is explained by this model?


e. What point estimate of AS would you make for a city where INC  $23,175 and POP  128.07? What would the approximate 95 percent confidence interval be?


8. Consider now that you have been asked to prepare a forecast of wholesale furniture sales for the entire United States. You have been given the monthly time-series data in

the accompanying table:


WFS is wholesale furniture sales in millions of dollars. It is not seasonally adjusted.

PHS measures new private housing starts in thousands. UR is the unemployment rate

as a percent. You believe that furniture sales are quite probably related to the general

state of the economy and decide to test whether the unemployment rate affects furniture sales. You expect that as the unemployment rate rises (and the economy thus shows some sign of difficulty), furniture sales will decline.


a. Summarize the results of your bivariate regression by completing the following



b. After discussing the results at a staff meeting, someone suggests that you fit a

multiple-regression model of the following form:



M1  A dummy variable for January

M2  A dummy variable for February

M4  A dummy variable for April

M9  A dummy variable for September

M10  A dummy variable for October


Summarize the results in the following table:


• Do the signs of the coefficients make sense?

• Are the coefficients statistically significant at a 95 percent confidence level

(one-tailed test)?

• What percentage of the variation in WFS is explained by the model?


11. The data presented below are for retail sales in the United States quarterly from the

period 1992Q1 through 2003Q4. Also included is disposable personal income per

capita (DPIPC) (to use as a measure of the well-being of the economy).



a. Develop a regression model of retail sales as a function of the S&P 500. Comment

on the relevant summary statistics.


b. Estimate a new multiple-regression model using seasonal dummy variables for

quarters 2, 3, and 4. Additionally, add a time index to account for trend. Comment

on the relevant statistics of this model. Is this model an improvement on the model

above? What evidence is there that this second model provides an improvement (no



c. Square the time index variable and add it to the multiple-regression model above.

Does the resulting model perform better than either previous model? Explain your



13. This is a problem in model selection. A “big box” home improvement store has

collected data on its sales and demographic variables relating to its various stores. The

cross-sectional data set for these variables is below:





Sales  average monthly store sales (in thousands of dollars)

X1  Households in a 5-mile ring that are do-it-youselfers (in thousands)

X2  Average monthly advertising expenditures (in dollars)

X3  Square footage of competitor stores in a 5-mile ring (in thousands)

X4  Households in a 5-mile ring that are below the poverty level (in hundreds)

X5  Weighted average daily traffic count at store intersection


a. Begin by estimating a model with independent variables X1, X2, and X3. Comment on the appropriateness of this model and its accuracy.


b. Now add X4 to the model above and again comment on the appropriateness of the model. Has the accuracy improved?


c. Finally, add X5 to the model and again comment on the accuracy of the model. Use the appropriate summary statistics of the three models to suggest which of the five independent variables should be in the model. Advise the “big box” retailer on which characteristics are important when choosing new store locations.

Calculate the price of your order

550 words
We'll send you the first draft for approval by September 11, 2018 at 10:52 AM
Total price:
The price is based on these factors:
Academic level
Number of pages
Basic features
  • Free title page and bibliography
  • Unlimited revisions
  • Plagiarism-free guarantee
  • Money-back guarantee
  • 24/7 support
On-demand options
  • Writer’s samples
  • Part-by-part delivery
  • Overnight delivery
  • Copies of used sources
  • Expert Proofreading
Paper format
  • 275 words per page
  • 12 pt Arial/Times New Roman
  • Double line spacing
  • Any citation style (APA, MLA, Chicago/Turabian, Harvard)

Our guarantees

Delivering a high-quality product at a reasonable price is not enough anymore.
That’s why we have developed 5 beneficial guarantees that will make your experience with our service enjoyable, easy, and safe.

Money-back guarantee

You have to be 100% sure of the quality of your product to give a money-back guarantee. This describes us perfectly. Make sure that this guarantee is totally transparent.

Read more

Zero-plagiarism guarantee

Each paper is composed from scratch, according to your instructions. It is then checked by our plagiarism-detection software. There is no gap where plagiarism could squeeze in.

Read more

Free-revision policy

Thanks to our free revisions, there is no way for you to be unsatisfied. We will work on your paper until you are completely happy with the result.

Read more

Privacy policy

Your email is safe, as we store it according to international data protection rules. Your bank details are secure, as we use only reliable payment systems.

Read more

Fair-cooperation guarantee

By sending us your money, you buy the service we provide. Check out our terms and conditions if you prefer business talks to be laid out in official language.

Read more