# Regression analysis

Always get overwhelmed by the amount of material when covered at a comprehensive level. Attached is the study material of what to be prepared to cover at the conclusion of this course. I have worked through them but get stumped at several points. Can you provide a systematic approach to these problems and provide a reference to refer to make sure my solutions are accurate. It would helpful if you can explain why you did what you did, as this is just a helpful of study and questions may appear differently at the actual conclusion of the course.

Enterprise Industries produces Fresh, a brand of laundry detergent. In order to more effectively manage its inventory and make revenue projections, the company would like to better predict demand for Fresh. To develop a prediction model, the company has gathered data concerning demand for Fresh over the last 16 sales periods (each sales period is defined to be a four-week period).

The variables assigned for this problem are:

Y=the demand for the large size bottle of Fresh (in hundreds of thousands of bottles) in the sales period.

Part A

Analyze the above output to determine the multiple regression equation.

Part B

X1=the price (in dollars) of Fresh as offered by Enterprise Industries in sales period.

X2=the average industry price (in dollars) of competitor's similar detergents in the sales period. X3= Enterprise Industries' advertising expenditure (in hundreds of thousands of dollars) to promote Fresh in the sales period.

Refer to Table 12C on the Handout for MegaStat output.

What conclusions are possible using the result of the global usefulness test (F test)?

Part C

What conclusions are possible using the results of the t-tests of the independent variables (alpha=0.05. two tailed. Does this data provide significant evidence (alpha=0.0) that demand (n hundreds of thousands of bottles) is associated with price (n dollars) and/or average industry price (in dollars) and/or advertising expenditure (n hundreds of dollars? Find the p-values and interpret.

Part D

Using the table above, predict the demand when the price is $3.70 the average industry price is $3.90, and the advertising expenditure is $650,000.

https://brainmass.com/statistics/regression-analysis/regression-analysis-168522

#### Solution Summary

Step by step method for regression analysis is discussed here. Regression coefficients, coefficient of determination, scatter diagram and significance of regression model are explained in the solution.