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DAT 565 Wk 5 Discussion - Patterns and Modeling 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.