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Part II: Making Predictions by Using Regression
Suppose you’re in the marketing department for a major national company
that sells plasma TVs. You want to sell as many TVs as you can, so you want
to figure out which factors play a role in plasma TV sales. In talking with your
advertising people and remembering what you learned in those college
classes on business, you know that one powerful way to get sales is through
advertising. You think of the types of advertising that may be related to sales
of plasma TVs and your team comes up with two ideas:
TV ads: Of course, how better to sell a TV than through a TV ad?
Newspaper sales: Hit ’em on Sunday when they’re watching the game
through squinty eyes that are missing all the good plays and the terrible
calls the referees are making.
By coming up with a list of possible x variables to predict y, you have just
completed step one of a multiple regression analysis, according to the list in
the previous section. Note that all three variables I use in the TV example are
quantitative (the TV ad and newspaper sales variables and the TV sales
response variable), which means you can go ahead and think about a multi-
ple regression model by using the two types of ads to predict TV sales.
Collecting the data
Step two in the multiple regression analysis process is to collect the data for
your x and y variables. To do this, make sure that for each individual in the
data set, you collect all the data for that individual at the same time (including
the y-value and all x-values) and keep the data all together for each individ-
ual, preserving any relationships that may exist between the variables. You
must then enter the data into a table format by using Minitab or any other
software package (each column represents a variable and each row repre-
sents all the data from a single individual) to get a glimpse of the data and to
organize it for later analyses.
To continue with the TV sales example from the preceding section, say that
you start thinking about all the reams of data you have available to you
regarding the plasma TV industry. You remember you’ve worked with the
advertising department before to do a media blitz by using, among other
things, TV and newspaper ads. So you have data on these variables from a
variety of store locations. You take a sample of 22 store locations in different
parts of the country and put together the data on how much money was
spent on each type of advertising, along with the plasma TV sales for that
location. You can see the data in Table 5-1.