Birth month is related to success in many youth sports. This is known as the relative age effect (RAE). The RAE in youth sports is exhibited by the presence of fewer members of an age group born in the months further from the age-cutoff date for the sport (January 1 for most youth soccer leagues). These older players, due to their physical and psychological advantages, are more likely to be identified as talented and therefore are selected for advancement in the youth soccer academies. While these differences are crucial in the selection process during adolescence, is there evidence that RAE carries over to adult players? In this problem we examine whether RAE exists in the top level European soccer leagues: Ligue 1 and Ligue 2 in France, Bundesliga 1 and Bundesliga 2 in Germany, Seire A and Serie B in Italy, Premier League and Championship in England, and 1st Division and 2nd Division in Spain. The second column in the table below shows the number of birthdays by month of 5507 male players who played during a recent season in the leagues mentioned above. Shown in the third column, based on national demographic statistics, is the percentage of the general population born in each month. Does the distribution of birth months of elite European soccer players differ from the distribution of birth months of the general population? Perform the appropriate hypothesis test. Number of Birthdays and Expected Number of Birthdays by Month in Top Two Levels of European Soccer Month Observed Birthdays General Population % Expected Birthdays January 593 8% 440.56 February 549 7% 385.49 March 581 8% 440.56 April 497 8% 440.56 May 503 8% 440.56 June 450 8% 440.56 July 403 9% 495.63 August 434 9% 495.63 September 414 9% 195.63 October 365 9% 495.63 November 364 8% 440.56 December 354 9% 195.63 Total 5507 100% 5507 Question 1. In the calculation of the test statistic for this hypothesis test, what numerical value does the month of October contribute to the test statistic? (round to 2 decimal places) Question 2. What is the value of the test statistic for this hypothesis test? (round to 2 decimal places)October 365 9% 495.63 November 364 8% 440.56 December 354 9% 495.63 Total 5507 100% 5507 Question 1. In the calculation of the test statistic for this hypothesis test, what numerical value does the month of October contribute to the test statistic? (round to 2 decimal places) Question 2. What is the value of the test statistic for this hypothesis test? (round to 2 decimal places) Question 3. Choose the correct expression for the P-value for this hypothesis test. O P-value 0.20 O 0.05