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Interpreting Data for Income Levels vs. Prices Paid for Cars

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Look at the data below for the income levels and prices paid for cars for ten people:

Annual Income Level Amount Spent on Car

38,000 12,000
40,000 16,000
117,000 41,000
17,000 3,500
23,000 6,500
79,000 21,000
33,000 5,000
66,000 8,000
15,000 1,500
52,000 6,000

A. What kind of correlation do you expect to find between annual income and amount spent on car? Will it be positive or negative? Will it be a strong relationship? Base your answer on your personal guess as well as by looking through the data.

B. What is the direction of causality in this relationship - i.e. does having a more expensive car make you earn more money, or does earning more money make you spend more on your car? In other words, define one of these variables as your dependent variable (Y) and one as your independent variable (X).

C. What method do you think would be best for testing the relationship between your dependent and independent variable, ANOVA or regression? Explain your reasoning thoroughly with a discussion of both methods.

D. Go to this calculation page and enter in your data in the X and Y columns (don't use commas, enter 8,000 as 8000). Then click on the button "Y=MX B". Then click on the "graph" button. Write out your equation as calculated, along with your coefficients. Discuss the significance and interpretation of this result, and discuss your graph.

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Solution Summary

The solution analyzes and interprets data for income levels vs. prices paid for cars.

Solution provided by:
Sandhya Sharma, MSc
Education
  • BSc, Meerut University
  • MSc, Meerut University
  • MPhil, Institute of Advanced Studies
  • MSc, AIT
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