Question #97239

Packages have a nominal net weight of 1 kg. However their actual net weights have a uniform distribution over the interval 980 g to 1030 g. a) Find the probability that the net weight of a package is less than 1 kg. b) Find the probability that the net weight of a package is less than w g, where 980 < w < 1030. c) If the net weights of packages are independent, find the probability that, in a sample of five packages, all five net weights are less than wg and hence find the probability density function of the weight of the heaviest of the packages.

Expert's answer

We know that XU(980,1030)X \sim U(980,1030) with probability density( a=980a = 980 and b=1030b = 1030)


pX(x)={0x[a,b]1bax[a,b]{p_X}(x)=\begin{cases} 0 & x \notin [a,b] \\ \frac{1}{{b - a}} & x \in [a,b]\end{cases}

Let's find the probability density as

FX(x)=P(X<x)=xpX(ξ)dξ{F_X}(x) = P(X < x) = \int\limits_{ - \infty }^x {{p_X}(\xi )d\xi }

At the interval x(,a]x \in ( - \infty ,a] we get FX(x)=x0dξ=0{F_X}(x) = \int\limits_{ - \infty }^x {0d\xi } = 0

At the interval x[a,b]x \in [a,b] we get FX(x)=ax1badξ=ξbaax=xaba{F_X}(x) = \int\limits_a^x {\frac{1}{{b - a}}d\xi } = \left. {\frac{\xi }{{b - a}}} \right|_a^x = \frac{{x - a}}{{b - a}}

At the interval x[b,+)x \in [b, + \infty ) we get FX(x)=baba+b+0dξ=1{F_X}(x) = \frac{{b - a}}{{b - a}} + \int\limits_b^{ + \infty } {0d\xi } = 1

Thus we get


FX(x)={0x<abxbaaxb1x>b{F_X}(x)=\begin{cases} 0 & x <a \\ \frac{{b - x}}{{b - a}} & a \leqslant x \leqslant b \\ 1 & x > b \end{cases}

a) We asked to find P(X<1000)P(X < 1000)


P(X<1000)=F(1000)=10009801030980=25P(X < 1000) = F(1000) = \frac{{1000 - 980}}{{1030 - 980}} = \frac{2}{5}

b) We asked to find P(X<w)P(X < w) if w(980,1030)w \in (980,1030)


P(X<w)=F(w)=w9801030980=w98050P(X < w) = F(w) = \frac{{w - 980}}{{1030 - 980}} = \frac{{w - 980}}{{50}}

c) Let YY be the number of packages that weight less than ww , because the events are independent YY is distributed according to the Binomial distribution YB(n,p)Y \sim B(n,p) with n=5n = 5 and p=P(X<w)=w98050p = P(X < w) = \frac{{w - 980}}{{50}}. The probability mass function for binomial distribtion is


pY(k)=Cnkpk(1p)nk{p_Y}(k) = C_n^k{p^k}{(1 - p)^{n - k}}

where Cnk=n!k!(nk)!C_n^k = \frac{{n!}}{{k!(n - k)!}} - binomial coefficient. Thus, the probability that all 5 net will weight less than ww


P(Y=5)=pY(5)=5!5!0!(w98050)5(1w98050)0=(w98050)5P(Y = 5) = {p_Y}(5) = \frac{{5!}}{{5!0!}}{(\frac{{w - 980}}{{50}})^5}{(1 - \frac{{w - 980}}{{50}})^0} = {(\frac{{w - 980}}{{50}})^5}

Now we need to find the probability density for the heaviest package if we know that all 5 packages are weight less than ww . Actually, at the previous step we found the conditional probability


P(X<wY=5)=(w98050)5P(X < w|Y = 5) = {(\frac{{w - 980}}{{50}})^5}

Using is we can easily found it


f(w)=P(X<wY=5)w=w(w98050)5=110(w98050)4{f}(w) = \frac{{\partial P(X < w|Y = 5)}}{{\partial w}} = \frac{\partial }{{\partial w}}{(\frac{{w - 980}}{{50}})^5} = \frac{1}{{10}}{(\frac{{w - 980}}{{50}})^4}

(of course, for 980<w<1030980 < w < 1030 )


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