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14/08/2020 Client: sarahhitz Deadline: 10 Days

 


Models help us describe and summarize relationships between variables. Understanding how process variables relate to each other helps businesses predict and improve performance. For example, a marketing manager might be interested in modeling the relationship between advertisement expenditures and sales revenues.


Consider the dataset below and respond to the questions that follow:


Advertisement ($'000)   Sales ($'000)


1068    4489


1026    5611


767      3290


885      4113


1156    4883


1146    5425


892      4414


938      5506


769      3346


677      3673


1184    6542


1009    5088



  • Construct a scatter plot with this data.

  • Do you observe a relationship between both variables?

  • Use Excel to fit a linear regression line to the data. What is the fitted regression model? (Hint: You can follow the steps outlined on page 497 of the textbook.)

  • What is the slope? What does the slope tell us?Is the slope significant?

  • What is the intercept? Is it meaningful?

  • What is the value of the regression coefficient,r? What is the value of the coefficient of determination, r^2? What does r^2 tell us?

  • Use the model to predict sales and the business spends $950,000 in advertisement. Does the model underestimate or overestimates ales?



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