4)
a) P(A car accident gets reported) = 12/40 = 0.3
b) The no. of cases getting reported follows a binomial distribution with p = 0.3 and n = 40
Hence, variance of no. of case reported = n*p*(1-p) = 40*0.3*0.7 = 8.4
=> Std deviation = sqrt(8.4) = 2.898 ~ 3
c) P(No case reported out of 5 accidents) = * 0.30 * 0.75 = 0.168
5) Let A = Event that Bank increased interest rate, B = Event that House prices increased
Using Baye's theorem:
P(Bank increased interest rate / House prices increased)
= P(A/B)
= P(B/A) * P(A) / ( P(B/A) * P(A) + P(B/Ac) * P(Ac) ), where Ac is the event that bank keeps interest rate the same
But, P(B/A) = 0.15, P(B/Ac) = 0.75
And, P(A) = 0.65, P(Ac) = 1 - 0.65 = 0.35
Plugging in the above values, we get
P(Bank increased interest rate / House prices increased) = 0.271
6)
P(A Canadian uses Google as main search engine) = 0.7206
a) P(At least one of the 10 doesn't use Google as main search engine)
= 1 - P(all of them use Google as main search engine)
= 1 - 0.720610 = 0.962
b) No. of individuals needed to survey before finding the first one who prefers search engine other than google follows a geometric distribution with p = 1 - 0.7206 = 0.2794 (probability of finding someone who prefers a search engine other than google). Let this variable be Y
Hence, E(Y) = (1-p) / p = 2.579
c) P(Exactly 3 do not use Google among the 10 individuals)
= * 0.27943 * 0.72067 = 0.264
d) The assumptions were that the event that the different individuals do not use or use Google as search engine are independent of each other. Also there are only 2 outcomes (prefer or do not prefer Google as main search engine) and no. of trials (individuals) is fixed (10 above).
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