Matt Kenseth won the 2012 Daytona 500, the most important race of the NASCAR season his win was no suprise because for the 2011 season he finished fourth in the point standing 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 finishing in 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 13.7 shows data for the 2011 season for the top 35 drivers (NASCAR website, February 28,2011).

Driver	Points	Poles	Wins	Top 5	Top 10	Winnings ($)
Tony Stewart	2403	1	5	9	19	6,529,870
Carl Edwards	2403	3	1	19	26	8,485,990
Kevin Harvick	2345	0	4	9	19	6,197,140
Matt Kenseth	2330	3	3	12	20	6,183,580
Brad Keselowski	2319	1	3	10	14	5,087,740
Jimmie Johnson	2304	0	2	14	21	6,296,360
Dale Earnhardt Jr.	2290	1	0	4	12	4,163,690
Jeff Gordon	2287	1	3	13	18	5,912,830
Denny Hamlin	2284	0	1	5	14	5,401,190
Ryan Newman	2284	3	1	9	17	5,303,020
Kurt Busch	2262	3	2	8	16	5,936,470
Kyle Busch	2246	1	4	14	18	6,161,020
Clint Bowyer	1047	0	1	4	16	5,633,950
Kasey Kahne	1041	2	1	8	15	4,775,160
A.J. Allmendinger	1013	0	0	1	10	4,825,560
Greg Biffle	997	3	0	3	10	4,318,050
Paul Menard	947	0	1	4	8	3,853,690
Martin Truex Jr.	937	1	0	3	12	3,955,560
Marcos Ambrose	936	0	1	5	12	4,750,390
Jeff Burton	935	0	0	2	5	3,807,780
Juan Montoya	932	2	0	2	8	5,020,780
Mark Martin	930	2	0	2	10	3,830,910
David Ragan	906	2	1	4	8	4,203,660
Joey Logano	902	2	0	4	6	3,856,010
Brian Vickers	846	0	0	3	7	4,301,880
Regan Smith	820	0	1	2	5	4,579,860
Jamie McMurray	795	1	0	2	4	4,794,770
David Reutimann	757	1	0	1	3	4,374,770
Bobby Labonte	670	0	0	1	2	4,505,650
David Gilliland	572	0	0	1	2	3,878,390
Casey Mears	541	0	0	0	0	2,838,320
Dave Blaney	508	0	0	1	1	3,229,210
Andy Lally*	398	0	0	0	0	2,868,220
Robby Gordon	268	0	0	0	0	2,271,890
J.J. Yeley	192	0	0	0	0	2,559,500

1. Develop appropriate descriptive statistics to summarize the data. Use proper graphitizing tools and tables to summarize your data. Interpret the descriptive statistics.

2. Suppose you wanted to predict Winnings ($) using only the number of poles won (Poles), the number of wins (Wins), the number of top five finishes (Top 5), or the number of top ten finishes (Top 10). which of these four variables provides the best single predictor of winnings?

3-) 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.

4-) create two new independent variables: Top 2-5 and Top 6-10. Top 2-5 represents the number of times the driver finished between second and fifth place and Top 6-10 represents the number of times the driver finished between sixth and tenth place. Develop an estimated regression equation that can be used to predict Winnings ($) using Poles, Wins, Top 2-5, and Top 6-10. Test for individual significance and discuss your findings and conclusions.

5-) Based upon the results of your analysis, what estimated regression equation would you recommend using to predict Winnings ($) ? Provide an interpretation of the estimated regression coefficients for this equation.

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