Looking for help with questions 1-7. If not too time consuming, a step-by-step explanation would be greatly appreciated.
YEAR DRIVER POINTS STARTS POLES WINS TOP_5 TOP_10 WINNING 2010 Bill Elliott 1107 13 0 1314990 2006 Bill Elliott 765 10 1056130 2007 Bill Elliott 1579 20 2056930 ooooo 2008 Bill Elliott 1528 20 1965750 booooooo oooooo 2007 Bobby Labc 3517 36 4586960 2006 Bobby Labc 3567 36 4651090 2009 Boris Said 152 160338 2008 Boris Said 194 3 260953 2006 Brian Vicke 3906 36 3917680 OH 2007 Brian Vicke 2065 23 2105820 2007 Carl Edward 6222 36 4611970 2010 Casey Mear 1573 21 1871550 2007 Casey Mea 3949 36 4179200 2009 Casey Mear 3759 36 3958460 2010 Clint Bowye 6155 36 PHONOOHOH 4700630 2007 Clint Bowye 6377 36 DOOOOOPOPNOHOWOP 4215870 OO OOOH OHOOOAUINOUOHHNOOWE 2006 Clint Bowye 3833 36 3924410 2008 Dale Earnha 6127 36 4611290 2009 Dave Blane 1204 30 2343060 2010 Dave Blane 1416 29 2326360 2006 Dave Blane 3259 36 3479640 x O 1 0 0 F J G N U Q O W O O O O N O N O N OO C H V O P O O U U DOOD WOOOO 2006 David Gillile 1178 15 1521450 2007 David Gillila 2924 36 4330840 2010 David Gillila 2445 32 3035140 2009 David Ragal 3252 36 3682210 2006 David Ragal 88 2 129610 2010 David Stren 825 11 o 946775 2008 David Stren 34 1 91525 2009 David Stren 2919 33 4141680 2007 David Stren 3163 36 3184560 2006 David Stren 2865 34 3456110 2008 Denny Ham 6214 36 5494360 2009 Elliott Sadle 3350 36 3819100 2007 Elliott Sadle 3140 36 3972990 HNNOON 2006 Greg Biffle 4075 36 4602720 2008 Greg Biffle 5467 36 4906160 JW WODHON NUN OOH NOOOOO 2007 Greg Biffle 3991 36 4397950 2008 Jeff Burton 6335 36 5542180 VOUOHNOOHNANNOOHOO 2006 Jeff Burton 6228 36 5008880 2010 Jeff Burton 6033 36 5178400 2007 Jeff Gordon 5646 36 7148620 NVC 2006 Jeff Gordon 5256 36 5975870 2009 Jeff Gordon 6473 36 25 6476460 2008 Jeff Gordon 5316 36 5944140 2006 Jimmie Johi 6475 36 24 8909140 2010 Jimmie Joh 6622 36 23 7264780 2009 Jimmie Johi 6652 36 16 24 73396301. Use your study in Statistical Inferences, and the sample NASCAR data you are given, please estimate the amount of money an average driver makes winning NASCAR tournaments. From previous studies, you know that the standard deviation of NASCAR winnings is $2.222 million. For your work: a) Identify what strategy/formula you use b) Calculate the average money won by an average NASCAR driver. Be 95%% confident in your calculation. c) Explain/interpret your answer 2. Use your study in Statistical Inferences, and the sample NASCAR data you are given, please estimate the percent of times Ford cars are driven in NASCAR tournaments. You want to answer with 90% confidence. a) Identify what strategy/formula you use b) Calculate the average money won by an average NASCAR driver. Be 95%% confident in your calculation. c) Explain/interpret your answer 3. Use your study in Determining Relationships, to answer the following scenario. The NASCAR CEO believes that drivers who drive Ford cars, as compared to any other car, win more money. He tasks you to verify this using the sample NASCAR data you have. Hint: categorize your sample data into Ford driven cars and non-Ford. Also, for every driver categorize the driver based on whether he/she won less than the average winnings or more than the average winnings (average included). For your work: a) Identify what strategy/formula you use. b) Test if Ford drivers make more than average winnings. Use 95% confidence. c) Explain/interpret your answer d) Show a plot of your results. Make sure it has a title, legend, axes named. 1. Use your study in Determining Relationships, to test whether there is a relationship among any pair of numeric variables in the NASCAR data. Interpret the answers you find for every relationship. For the strongest relationship and the weakest relationship plot the data and discuss it. Explain if the plot shows the relationship index you calculated 5. Use the regression analysis output in the worksheet NASCAR Regression. a)Interpret the regression results. Make sure you discuss the R2, coefficients, identify the significant variables. b) Using your analysis, list the top 3 factors you will use in your advertisement to attract more NASCAR drivers. c) Now add the Ford car to the regression model. Does the model improve? By how much? Can the CEO advertise that drivers should drive Ford cars because they will make more money? 6. Use your study in Finding Differences to test whether the average driver drove the same number of laps when driving Ford cars, as compared to when driving Dodge cars. Be 90% confident in your answer. 7. Use your study in Finding Differences to test whether Toyota cars are driven as frequently as Chevy cars. Interpret your answer. Be 95%% confident in your analysis.SUMMARY OUTPUT Regression Statistics Multiple R 0.957432522 R Square 0.916677034 Adjusted R Square 0.912510886 Standard Error 600910.0729 Observations 190 ANOVA of 55 MS F Significance F Regression 9 7.15E+14, 7.95E+13 220.0299 3.54614E-92 Residual 180 6.5E+13] 3.618+11 Total 189 7.8E+141 Coefficients andard Erro t Stat P-value Lower 95% Upper 95% lower 95.0%Upper 95.0% Intercept 30404.49328 781984 -0.03888 0.969028 -1573439.392 1512630 -1573439 1512630 POINTS -78.08473409 92.46174! -0.84451 0.399506 -260.5330818 104.3636 -260.533 104.3636 STARTS 76478.72308 15134.761 5.053183 1.06E-06 46614.3424 106343.1 46614.34 106343.1 POLES -40064.1891 38994.44 -1.02743 0.305595 -117009.2127 36880.83 -117009 36880.83 WINS 205975.8788 44413.13 4.637725 6.75E-06 118338.5314 293613.2 118338.5 293613.2 TOP_10 78947.18153 21195.24! 3.72476 0.000261 37124.08651 120770.3 37124.09 120770.3 AVG_ST -8910.66609 13489.651 -0.66056 0.509742 -35528.85448 17707.52 -35528.9 17707.52 LAPS 111.1087178 54.03331 2.0563 0.041197 4.488528342 217.7289 4.488528 217.7289 LED 42.78290972 236.4279, 0.180955 0.856606 -423.7439824 509.3098 -423.744 509.3098 RATING 6095.616137 8791.049 0.693389 0.488959 -11251.15296 23442.39 -11251.2 23442.39
