DMD Assignment 1. (3.7) (a) firstly, suppose it is standardly distribution, we roll in the hay the mean of the love apples saddle is 4.2(µ=4.2), the unoriginal excursion is 1.0(?=1.0). Assume that the weight of tomato is dependent. The tomatoes are sell in package of three. ?~N(nµ, ?n?). E(?)=3*µ=12.6 ?(?)= ?3*?=1.7321 (b) P(11.0???13.0)=P{(11-12.6)/1.7321?(?-E(?))/?(?) ?(13.0-12.6)/1.7321} =0.5910-0.1788=0.4122=41.2% 2. (3.9) Let X foretell the region increase in the Dow Jones Index. Let Y have-to doe with the parting increase in S& adenine;P five hundred index. thinking X and Y succeed a conjugation Normal distribution. The mean of X is 11% (µx=0.11), the standard aberration of X is 13% (?x=0.13). the mean of Y is 10%(µy=0.10), the standard deviation of Y is 12% (?y=0.12). Suppose CORR(X,Y)=0.43. (a)P(X?0.11)=1-P{(X-µx)/ ??(0.11-0.11)/0.13} =1-F (0) =1/2=50% (b)P(X?-0.11)=P{(X-µx)/?x?(-0.11-0.11)/0.13} =F(-1.69)=0.0455=45.5% (c)P(0?Y?0.15)=P{(X-µy)/?y?(0.15-0.10)/0.12}-P{(X-µy)/?y?(0-0.10)/0.12} =0.6628-0.20=46.3% (d) Suppose A is the portfolio of Dow Jones index and S&P index. So, E(A)=0.3*0.11+0.7*0.10=0.103 Var(A)=0.32*0.132+0.72*0.122+2*0.3*0.7*0.43*0.13*0.12=0.01138 ?(A)=0.1067 (e) (X-Y) alike come afters Normal distribution. µ(x-y) =0.01, ?(x-y) =0.13. (X-Y)~N (0.01, 0.

13) P{ (X-Y) ?0}=1-P{ (X-Y)- µ(x-y)/ ?(x-y)?(0-0.01)/0.13}=1-F(-0.0415)=0.532=53.2% 3. (3.15) (a) We quite a little see from the core of the problem, train and infer that the amount of X ~ Binomial (n, p). So, assume S=X1+X2++Xn, n=2 cholecalciferol, p=0.1. E(S) = n*p=250, ?s= 15 (b) Revenue: assume Y be the returned revenue item. Y~ Binomial (n, p). E( Y) =500*250-Sn*500=125,000-500*Sn =1125000; ?y=335.4 (c ) assume the Z be the item, P(Z?1,300,000) =1-P(Z?1,300,000-1125000/335.4) =1-P(521.77)=0 4.(3.18) (a) The assumptions are that the chance of hazardous problem happened is in depended from each other, and also obey the identically distribution. The assumptions appear to be...If you take to get a upright essay, put up it on our website:
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