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University of Phoenix Patterns and Modeling Report

Question Description

I’m working on a data analytics exercise and need an explanation to help me study.

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 advertising expenditures and sales revenues.

Consider the following dataset:

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 and answer the following questions:

  • What is the fitted regression model?
  • 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 if the business spends $950,000 on advertising. Does the model underestimate or overestimate sales?

Prepare your graphical and written response in no less than 500 words.

Advertising ($’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

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