Navigation » List of Schools, Subjects, and Courses » DAT 565 – Data Analytics and Business Analysis » Discussion » Wk 5 Discussion – Patterns and Modeling [due Day 3]
With Answers Good news! We are showing you only an excerpt of our suggested answer to this question. Should you need our help in customizing an answer to this question, feel free to send us an email at or chat with our customer service representative.
Wk 5 Discussion – Patterns and Modeling [due Day 3]
Discussion Topic
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.
- 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 in Fitting a Regression on a Scatter Plot 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?
Due Day 7
Reply to at least 2 of your classmates or your faculty member. Be constructive and professional.