
Predicting Winnings for NASCAR Drivers
Matt Kenseth won the 2012 Daytona 500, the most important race of the NASCAR season. His win was no surprise because for the 2011 season he finished fourth in the point standings with 2330 points, behind Tony Stewart (2403 points), Carl Edwards (2403 points), and Kevin Harvick (2345 points). In 2011 he earned $6,183,580 by winning three Poles (fastest driver in qualifying), winning three races, finishing in the top five 12 times, and finishingin the top ten 20 times. NASCAR's point system in 2011 allocated 43 points to the driver who finished first, 42 points to the driver who finished second, and so on down to 1 point for the driver who finished in the 43rd position. In addition, any driver who led a lap received 1 bonus point, the driver who led the most laps received an additional bonus point, and the race winner was awarded 3 bonus points. But the maximum number of points a driver could earn in any race was 48. Table 15.8 shows data for the 2011 season for the top 35 drivers (NASCAR website, February 28, 2011).
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2. Develop an estimated regression equation that can be used to predict Winnings ($) given the number of poles won (Poles), the number of wins (Wins), the number of top five finishes (Top 5), and the number of top ten (Top 10) finishes. Test for individual significance and discuss your findings and conclusions.

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Chapter 15 Solutions
Essentials of Modern Business Statistics with Microsoft Office Excel (Book Only)
- 1. A consumer group claims that the mean annual consumption of cheddar cheese by a person in the United States is at most 10.3 pounds. A random sample of 100 people in the United States has a mean annual cheddar cheese consumption of 9.9 pounds. Assume the population standard deviation is 2.1 pounds. At a = 0.05, can you reject the claim? (Adapted from U.S. Department of Agriculture) State the hypotheses: Calculate the test statistic: Calculate the P-value: Conclusion (reject or fail to reject Ho): 2. The CEO of a manufacturing facility claims that the mean workday of the company's assembly line employees is less than 8.5 hours. A random sample of 25 of the company's assembly line employees has a mean workday of 8.2 hours. Assume the population standard deviation is 0.5 hour and the population is normally distributed. At a = 0.01, test the CEO's claim. State the hypotheses: Calculate the test statistic: Calculate the P-value: Conclusion (reject or fail to reject Ho): Statisticsarrow_forward21. find the mean. and variance of the following: Ⓒ x(t) = Ut +V, and V indepriv. s.t U.VN NL0, 63). X(t) = t² + Ut +V, U and V incepires have N (0,8) Ut ①xt = e UNN (0162) ~ X+ = UCOSTE, UNNL0, 62) SU, Oct ⑤Xt= 7 where U. Vindp.rus +> ½ have NL, 62). ⑥Xn = ΣY, 41, 42, 43, ... Yn vandom sample K=1 Text with mean zen and variance 6arrow_forwardA psychology researcher conducted a Chi-Square Test of Independence to examine whether there is a relationship between college students’ year in school (Freshman, Sophomore, Junior, Senior) and their preferred coping strategy for academic stress (Problem-Focused, Emotion-Focused, Avoidance). The test yielded the following result: image.png Interpret the results of this analysis. In your response, clearly explain: Whether the result is statistically significant and why. What this means about the relationship between year in school and coping strategy. What the researcher should conclude based on these findings.arrow_forward
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- Analyze the residuals of a linear regression model and select the best response. yes, the residual plot does not show a curve no, the residual plot shows a curve yes, the residual plot shows a curve no, the residual plot does not show a curve I answered, "No, the residual plot shows a curve." (and this was incorrect). I am not sure why I keep getting these wrong when the answer seems obvious. Please help me understand what the yes and no references in the answer.arrow_forwarda. Find the value of A.b. Find pX(x) and py(y).c. Find pX|y(x|y) and py|X(y|x)d. Are x and y independent? Why or why not?arrow_forwardAnalyze the residuals of a linear regression model and select the best response.Criteria is simple evaluation of possible indications of an exponential model vs. linear model) no, the residual plot does not show a curve yes, the residual plot does not show a curve yes, the residual plot shows a curve no, the residual plot shows a curve I selected: yes, the residual plot shows a curve and it is INCORRECT. Can u help me understand why?arrow_forward
- Algebra: Structure And Method, Book 1AlgebraISBN:9780395977224Author:Richard G. Brown, Mary P. Dolciani, Robert H. Sorgenfrey, William L. ColePublisher:McDougal LittellElementary AlgebraAlgebraISBN:9780998625713Author:Lynn Marecek, MaryAnne Anthony-SmithPublisher:OpenStax - Rice University

