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# Multiple Regression and Model Building for The Abalone Fancy Fish Company

Attached are the data and the multiple regression output.

The Abalone Fancy Fish Company sells exotic fish to high end restaurants throughout the East Coast. The sales manager wants to determine what, if any, relationship exists between the pounds of fish sold by 24 sales persons and two independent variables, namely the length of time (in years) the sales person has been with the company and the market share (in %).

Using the attached Minitab output write the regression equation, and explain the regression coefficients.

Regression equation:
y = [ ] + [ ]x1 + [ ]x2
*Round to four decimal places.

Interpretation of b0
A. This tells us the average years of experience of the sales force, holding constant the sales and the market share.
B. This values is determined by setting the independent variables = 0 and it has practical usefulness.
C. This tells us the average sales, holding constant the years of experience and the market share.
D. This says we are 95% confident that in the population each additional year of experience will result in a decrease in sales around this value, for a given market share.
E. This value is determined by setting the independent variables = 0 but there is no practical value, since 0 market share would not make sense for any viable business.

Interpretation of b1
A. This tells us that for each additional year of experience, we can expect a decrease in sales of 11.6073 pounds, holding the market share constant.
B. This tells us that with 5 years of experience and a market share of 3%, one can expect that there will be 216.245 pounds sold.
C. This tells us that for each additional % of market share, we can expect an increase of 21.7580 pounds sold, holding constant the years of experience.
D. This value has no practical interpretation.
E. This tells us that for each additional year of experience, we can expect an increase in sales of 11.6073 pounds, holding the market share constant.

Interpretation of b2
A. This tells us that for each additional % of market share, we can expect an increase of 21.7580 pounds of fish sold, holding the years of experience constant.
B. This tells us that for each additional % of market share, we can expect a decrease of 21.7580 pounds, holding constant the years of experience.
C. This tells us that for 5 years of experience and a market share of 3%, one can expect that there will be 216.245 pounds of fish sold.
D. This tells us that for each additional year of experience, we can expect an increase of 11.073 pounds of fish sold, holding the market share constant.
E. This value has no practical interpretation.

Interpretation of the Standard Error:
A. This tells us how much the sales will increase in pounds sold for each increase of 1 year of experience, holding constant the market share.
B. This tells us the mean sales we should expect for any specific number of years of experience and market share.
C. This tells us how much we should expect the longevity of a sales person with the company to increase for each increase in market share of 21.7580%.
D. This tells us how much the observed sales can vary from the predicted values.
E. This value has no practical importance.

#### Solution Preview

Regression equation:
y = [92.9345 ] + [11.6073]x1 + [21.7580] x2

Interpretation of b0:
E. This value is determined by setting the independent variables = 0 but there is no practical value, ...

#### Solution Summary

This solution provides the answers for the four question regarding regression and standard error.

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