The data provides information pertaining to the points scored, number of times on pole, number of wins, number of top 5 finishes, number of top 10 finishes and total earnings from winnings for 35 Formula 1 drivers (though the names are real, the numbers are fictional). Your task is as follows: 1. Utilizing the variables provided to you, what would be your regression equation if you want to predict winnings utilizing all the other variables except the driver name? Please use multiple regression for this. 2. Does the variable "Top 5" affect the relationship between "Top 10" and "Winnings"? Create a separate multiple regression table for this and interepret the outcome.

Top 5 5 1 Wins 1 3 0 3 1 0 4 1 1 0 3 3 2 0 3 1 1 2 4 3 3 1 0 2 1 1 0 0 Driver Points Poles Max Verstappen 2393 Pierre Gasly 2393 Sergio Prez 2335 Felipe Nasr 2320 Fernando Alonso 2309 Charles Leclerc 2294 Lance Stroll 2280 Stoffel Vandoorne 2277 Kevin Magnussen 2274 Esteban Gutierrez 2274 Yuki Tsunoda 2252 Alexander Albon 2236 Guanyu Zhou 1037 Daniil Kvyat 1031 Nico Hlkenberg 1003 Daniel Ricciardo 987 Jolyon Palmer 937 Esteban Ocon 927 Lando Norris 926 Lewis Hamilton 925 Roy Nissany 922 Mick Schumacher 920 Sebastian Vettel 896 Pietro Fittipaldi Carlos Sainz 836 Nicholas Latifi 810 George Russell 785 Kimi Rikknen 747 Valtteri Bottas 660 Romain Grosjean 562 Robert Kubica 531 Nikita Mazepin Pascal Wehrlein 388 Callum Ilott 258 Antonio Giovinazzi 182 0 3 0 1 0 0 2 2 2 2 0 1 0 1 0 0 Top 10 Winnings (Euros) 9 19 36,730,518,750 19 26 47,733,693,750 9 19 34,858,912,500 12 20 34,782,637,500 10 14 28,618,537,500 14 21 35,417,025,000 4 12 23,420,756,250 13 18 33,259,668,750 5 14 30,381,693,750 9 17 29,829,487,500 8 16 33,392,643,750 14 18 34,655,737,500 4 16 31,690,968,750 8 15 26,860,275,000 1 10 27,143,775,000 3 10 24,289,031,250 4 8 21,677,006,250 3 12 22,250,025,000 5 12 26,720,943,750 2 5 21,418,762,500 2 8 28,241,887,500 2 10 21,548,868,750 4 8 23,645,587,500 4 6 21,690,056,250 3 7 24,198,075,000 2 5 25,761,712,500 2 4 26,970,581,250 1 3 24,608,081,250 1 2 25,344,281,250 1 2 21,815,943,750 0 0 15,965,550,000 1 1 18,164,306,250 0 0 16,133,737,500 0 0 12,779,381,250 0 0 14,397,187,500 Oooo 0 892 1 0 0 0 1 0 1 1 0 0 0 0 0 0 0 498 0 0 0 0 0 0 0 0