Description
Respond to the following in a minimum of 175 - 4oo 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 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 $950,000 in advertisement. Does the model underestimate or overestimates ales?
Explanation & Answer
Thank you so much
Running head: REGRESSION ANALYSIS
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Regression Analysis
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Institution Affiliation:
Date:
REGRESSION ANALYSIS
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Figure 1: The scatter plot
Sales vs advertisement costs
7000
y = 4.9216x - 25.168
R² = 0.6785
Sales ($'000)
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Advertisement ($ 000)
It is quite...