Analyze Complete Data

Now that your imputed values appear to be satisfactory, you are ready to run an analysis on the "complete" data. The dataset contains a variable Customer category [custcat] that segments the customer base by service usage patterns, categorizing the customers into four groups. If you can fit a model using demographic information to predict group membership, you can customize offers for individual prospective customers.

  1. Activate the telcoImputed dataset. To create a multinomial logistic regression model for the complete data, from the menus choose:

    Analyze > Regression > Multinomial Logistic...

    Figure 1. Multinomial Logistic Regression dialog
    Multinomial Logistic Regression dialog
  2. Select Customer category as the dependent variable.
  3. Select Marital status, Level of education, Retired, and Gender as factors.
  4. Select Age in Years, Years at current address, Years with current employer, Number of people in household, and Log of income as covariates.
  5. You want to compare other customers to those who subscribe to the Basic service, so select Customer category and click Reference category.
    Figure 2. Reference Category dialog box
    Reference Category dialog box
  6. Select First category.
  7. Click Continue.
  8. Click Model in the Multinomial Logistic Regression dialog box.
    Figure 3. Model dialog box
    Model dialog box
  9. Select Custom/Stepwise.
  10. Select Main effects from the Stepwise Terms Build Term(s) dropdown.
  11. Select lninc through reside as Stepwise Terms.
  12. Click Continue.
  13. Click OK in the Multinomial Logistic Regression dialog box.

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