To determine the expected profit of the manufacturer, we proceed as follows,
We first determine the following probabilities,
p(30<X<35)=p((30−33)/3<Z<(35−33)/3)
=p(−1<Z<0.67)=ϕ(0.67)−ϕ(−1)=0.7486−0.1587=0.5899
p(25<X⩽30)=p((25−33)/3<Z<(30−33)/3)
=p(−2.67<Z<−1)=ϕ(−1)−ϕ(−2.67)=0.1587−0.0038=0.1549
p(35⩽X<40)=p((35−33)/3<Z<(40−33)/3)
=p(0.67<Z<2.33)=ϕ(2.33)−ϕ(0.67)=0.9901−0.7486=0.2415
p(25<X⩽30 or (35⩽X<40))
=p(25<X⩽30)+p(35⩽X<40)=0.1549+0.2415=0.3964, since the two ranges are mutually exclusive.
p(X<25 orX>40)=1−(0.5899+0.3964)=0.0137
With these probabilities, let us form the table below.
Profit per unit probability
Rs 100 0.5899
Rs 50 0.3964
Rs -60 0.0137
Thus, the expeceted profit per unit is given as,
E(profit per unit)=Rs(100∗0.5899+50∗0.3964−60∗0.0137)=Rs 77.988≈Rs 78
Therefore, the expected profit of the manufacturer is Rs 78.
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