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# Regression Equation and Interpretation

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A CEO of a large pharmaceutical company would like to determine if he should be placing more money allotted in the budget next year for television advertising of a new drug marketed for controlling asthma. He wonders whether there is a strong relationship between the amount of money spent on television advertising for this new drug called XBC and the number of orders received. The manufacturing process of this drug is very difficult and requires stability so the CEO would prefer to generate a stable number of orders. The cost of advertising is always an important consideration in the phase I roll-out of a new drug. Data that have been collected over the past 20 months indicate the amount of money spent of television advertising and the number of orders received.

The use of linear regression is a critical tool for a manager's decision-making ability. Please carefully read the example below and try to answer the questions in terms of the problem context. The results are as follows:

Month Advertising Cost (thousands of dollars) Number of Orders
1 \$55.93 4,102,000
2 70.62 3,893,000
3 79.58 5,299,000
4 58.67 4,130,000
5 69.18 4,367,000
6 70.14 4,111,000
7 73.37 3,923,000
8 68.88 4,935,000
9 80.99 5,276,000
10 75.23 4,654,000
11 71.38 4,398,000
12 52.90 2,967,000
13 61.27 3,999,000
14 79.19 4,345,000
15 60.03 3,834,000
16 78.21 4,653,000
17 93.77 5,625,000
18 62.53 3,978,000
19 78.76 4,999,000
20 92.64 5,834,000

a. Set up a scatter diagram and calculate the associated correlation coefficient. Discuss how strong you think the relationship is between the amount of money spent on television advertising and the number of orders received. Please use the Correlation procedures within Excel under Tools > Data Analysis. The Scatterplot can more easily be generated using the Chart procedure.

b. Assuming there is a statistically significant relationship, use the least squares method to find the regression equation to predict the advertising costs based on the number of orders received. Please use the regression procedure within Excel under Tools > Data Analysis to construct this equation.
c. Interpret the meaning of the slope, b1, in the regression equation.
d. Predict the monthly advertising cost when the number of orders is 4,999,000. (Hint: Be very careful with assigning the dependent variable for this problem)
e. Compute the coefficient of determination, r2, and interpret its meaning.
f. Compute the standard error of estimate, and interpret its meaning.

https://brainmass.com/math/interpolation-extrapolation-and-regression/regression-equation-and-interpretation-56648

#### Solution Preview

a. Set up a scatter diagram and calculate the associated correlation coefficient. Discuss how strong you think the relationship is between the amount of money spent on television advertising and the number of orders received. Please use the Correlation procedures within Excel under Tools > Data Analysis. The Scatterplot can more easily be generated using the Chart procedure.

After copying the date, paste them into the Excel file, which I have created. You then select the whole area. Go to the Chart Wizard icon, select Scatter diagram, and the end result is presented in the following diagram.

Then use the formula CORREL in Excel to calculate the correlation coefficient. I have done so at the bottom of the column. The correlation coefficient found is 0.86.
In statistics, if the correlation coefficient is higher than 0.8 than there is a relatively strong dependence of the two variables. So in this case the dependence of order on advertising spending is relatively significant. (Note if the coefficient is larger than 0.9 than the relationship is very strong)

b. Assuming there is a statistically significant relationship, use the least squares method to find the regression equation to predict the advertising costs based on the number of orders received. Please use the regression procedure within Excel under Tools > Data Analysis to construct this equation.
First select the chart, then click on Chart menu, then Add trendline then select Linear, then go to the Options tab, then select Display equation on chart and Display R2 value. ...

#### Solution Summary

The solution provides detailed calculations and explanations for the problem. It includes a 5-page Word file and an Excel document for calculations and plots.

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