Step 1: Read - Review lCase Problem 2: Predicting Winnings for NASCAR Drivers i, from Chapter 15 of the ebook. Step 2: Do - Run a Regression for the Data File NASCAR {Chapter 15] using the video How to Add Excel": Data Analysis ToolPakd' for assistance. In a managerial report, - Suppose you wanted to predict Winnings (33] using only the number of poles won (Poles), the number of wins ['Il'lllinsjr the number of top ve nishes (Top 5)r or the number of top ten nishes {Top 10). Which of these four variables provides the best single predictor of winnings? - Develop an estimated regression equation [look at Equation 15.6 in our textbook as an example] that can be used to predict Winnings {$1 given the number of poles won {Poles}, the number of wins {'Iu'll'ins)r the number of top ve nishes [Top 5L and the number of top ten {Top 10} nishes. Test for individual signicance, and then discuss your ndings and conclusions: Step 3: Discuss: - What did you nd in your analysis of the data? Were there any surprising results? What recommendations would you make based on your ndings? Include details from your managerial report to support your recommendations. Guided Response: Review several of your peer's posts. In a minimum of 100 words each, respond to at least two of your fellow students' posts in a substantive manner, and provide information that they may have missed or may not have considered regarding the application of Multiple Regression in business and economics. Do you agree with their conclusions? Why or why not? You are encouraged to post your required replies earlier in the week to promote more meaningful and interactive discourse in this discussion fonJm. Continue to monitor the discussion forum until 11:55I pm. [Pacic time} on Day 3', and respond with robust dialogue to anyone who replies to your initial post