# Project #156327 - one question

 Subject Business Due By (Pacific Time) 11/26/2016 12:00 am

1.   Regression analysis:

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. Here are the results of the data collection.

 Month Advertising cost (in thousands) # of orders 1 \$68.93 4,902,000 2 72.62 3,893,000 3 79.58 5,299,000 4 58.67 4,130,000 5 69.18 4,367,000 6 70.14 5,111,000 7 83.37 3,923,000 8 68.88 4,935,000 9 82.99 5,276,000 10 75.23 4,654,000 11 81.38 4,598,000 12 52.9 2,967,000 13 61.27 3,999,000 14 79.19 4,345,000 15 80.03 4,934,000 16 78.21 4,653,000 17 83.77 5,625,000 18 62.53 3,978,000 19 88.76 4,999,000 20 72.64 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 Scatterplot and Correlation procedures within Excel under Tools > Data Analysis

b)   What is the regression equation?

c)    Interpret the meaning of the slope, b1, in the regression.

d)   Predict the monthly advertising cost when the # of orders is 5,100,000.

e)   Compute the coefficient of determination, r2, and interpret its meaning.

f)     Compute the standard error of estimate, and interpret its meaning.

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