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Consumer research presentation

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Consumer research presentation

  1. 1.  Consumer Research, Inc. Team #4
  2. 2. Descriptive Statistics
  3. 3. Scatter Diagram
  4. 4. Regression (Income as independent variable)
  5. 5. Scatter Diagram
  6. 6. Regression (Household size as independent variable)
  7. 7. Estimated Regression Equation
  8. 8. Prediction  Predicted annual credit card charge for a three- person household with an annual income of $40,000. AMOUNT = 1305 + 33.1 ($40) + 356 (3) AMOUNT = 1305 + 1324 + 1068 AMOUNT = 3697
  9. 9. Independent variables that could be added to the model. Perhaps we could add some qualitative independent variables that could describe some characteristics of the consumers regarding their credit card charges. Now, bear in mind that the standard error of the estimate is somewhat large for this model, and that might be corrected by the introduction of some other variables that complete this model and that correct the problem of multicollinearity. Here are some of those possible variables:  Average age of household. Independent variable that can give us additional refining to the model.  Purchase preference: cash or credit (qualitative variable). Dummy variable that can add some more precision into the model if done properly, and it is not correlated with the other proposed since it is the only one to involve cultural habits; therefore, it has to do with the introduction of a qualitative variable.  Male or Female and its subsequent percentage (qualitative variable). Data easy to collect, and one that can help us big time in refininf the model.
  10. 10. References  Fundamentals of Business Statistics, Fifth Edition. Deniss J. Sweeney, Thomas A. Williams, David R. Anderson.

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