Post a total of 3 substantive responses over 2 separate days for full participation. This includes your initial post and 2 replies to other students or your faculty member.

Due Day 3

Respond to the following in a minimum of 175 words:

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 using Excel (Attach the excel page).
• Do you observe a relationship between both variables? (Post your response in Blackboard).
• 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.) (Should be on the same Excel page).
• What is the slope? What does the slope tell us? Is the slope significant? (Post your response in Blackboard).
• What is the intercept? Is it meaningful? (Post your response in Blackboard).
• What is the value of the regression coefficient? What is the value of the coefficient of determination, r^2? What does r^2 tell us? (Post your response in Blackboard).
• Use the model to predict sales and the business spends $950,000 in the advertisement. Does the model underestimate or overestimate sales? Justify your answer. (Post your response in Blackboard).