Buad 310 Case Analysis Instruction

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BUAD 310 Spring 2013 Case
Due by 4PM on Friday, May 3rd (in BRI 400C)

In this case you will apply statistical techniques learned in the Regression part of BUAD 310.

Please read the following instructions carefully before you start:

• This assignment uses data from the file MagAds13S.XLS, which you can download from Blackboard. After you download the file go to Data → Load data → from file in StatCrunch to open it (you don’t need to change any of the options when loading this data.)

• The entire report should be typed and clearly presented without typos and grammatical errors. Copy and paste the relevant (explained further in more detail) regression output into your document. Do not attach any graphs.

• You are encouraged to work in groups (maximum size is 5). Any group submits only one report, in which the first page should have all the names and USC ID of the group members. A hard copy of the report needs to be submitted (an electronic copy is NOT acceptable). Before May 3rd, you can also hand in the report during class. When I am not in my office (BRI 400C), please drop the report in the office through the gap between the door and floor.

• Very important: present the problems in exactly the same order as they are listed.

• A note to Mac user: you might need to hold “shift” when selecting variables for the X-variables with multiple linear regression in StatCrunch.

Magazine Advertising

What factors influence the price of advertisements in magazines? Suppose you are part of a team of consultants hired by a retail clothing company wishing to place advertisements in at least one magazine. They are curious about what types of costs they can expect for magazines with different readership bases so they most effectively utilize their advertising budget. Your team has collected cost data on 44 consumer magazines. In addition, your team has measured some other characteristics of the magazines and their audiences that may be useful in understanding the advertisement costs better. The variables are as follows,

pagecost: Cost of a four-color, one-page ad (in dollars)
circ: Circulation (projected, in thousands)
percmale: Percent male among the predicted readership
medianincome: Median household income of readership (in dollars)

Some natural logarithms of the variables are also provided for your convenience. Your goal is to analyze the data with StatCrunch using Multiple Linear Regression methods and choose the best model to explain the differences in advertising costs between the different titles, and then to predict what the retail clothing company should expect to pay for advertising in the different magazines.

Answer the following questions (with reasonable detail, not just “yes” or “no”, use one or two sentences per question).

1. Visually examine the scatter plots of the response variable, pagecost, versus each of the explanatory variables (circ, percmale, medianincome). In StatCrunch you can go to [Graphics( Scatter Plot] to do each plot. Describe the form and the direction of each relationship. Do not attach any graphs.

2. Perform a Regression analysis to predict pagecost using all three explanatory variables

[Stat ( Regression ( Multiple Linear, then fill in the proper Response and Predictor variables, then click Next twice and under Save options select Residuals, Predicted values and 95% interval for either the mean or an individual (you will have to decide which one you need for part d!). For the CI (or PI) to be produced you need to enter the values from part d in the row underneath the data table, in appropriate columns. Note that the value for circ has to be entered in the same units as all the values in the circ column. To produce a residual plot do a Scatter plot as in question 1, selecting Residuals as the Y variable and Predicted values as the X variable].

Include the regression output, but not...
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