need some detailed steps for this

Crash Day 193 49 23 21 55 28 57 Before After 1. The numbers in the Figure above indicate the weather (overcast or not) of 434 location- matched triplets of days, one day on which a traffic accident took place, and two control days without an accident (the day before the accident and the day after the accident). This dataset could be analyzed as a 1:2-matched case-control. The Venn diagram presentation of the data is rather unconventional. In matched case-control studies the data could alternatively be presented in 2 x 2-tables exposed unexposed case bi control Ci di for each matched set i = 1,. ... 434. We denote n = a; t b; t c t di. (a) [5 Marks] We note that there are six types of location-specific 2 x 2-tables with the same exposure-case configuration. List these tables (i.e. different combinations of the numbers ai, bi, c; and di) and their counts.(b) [3 Marks] The null hypothesis assumes that there is no relationship between being a case and being exposed. Under the null hypothesis the distribution of the cell count a; conditional on the row and column marginals is hypergeometric. Find E(q; | 4; + q) and Var(a; [ a; + c) under the null. (c) [3 Marks] Test the null hypothesis of no association between weather and accidents using the Cochrane-Mantel-Haenszel (CMH) test statistic, given by CMla -[M Elaila + c)) Ell Var(a; | a; + Gi) which is asymptotically distributed as x' with one degree of freedom. Note: Xo.9s (1) = 3.84. (d) [4 Marks] Let's assume we have the following table is a triplet specific contingency table from a 1:2 matched case control study. exposed unexposed Total case control C d Total atc b+d The odds of being exposed in the case groups is o times of the odds of being exposed in the control group. Also, let's assume that P(@ = 1) = 14 00 and P(c = 1) = 1+ 0 Show that, P(a =1 [ a + c=1)= 2+0 (Hint: The 2 in the denominator comes from 2 controls)