Ceng 272 Statistical Computations
Midterm
Apr 06, 2011 14:40 - 16:30
Good Luck!
Answer all the questions.
Write the solutions explicitly and use the statistical terminology
  1. (5 pts) A rigged dice is known to have probability $1/2$ for the outcome 6 and all other outcomes are known to be equally likely. What is the probability for outcome 2?
  2. (10 pts) Suppose we have a group of 5 candidates
    i
    Find the number of ways selecting 3 council members.
    ii
    Find the number of ways selecting chair, vice chair, and treasurer from the group of 5 candidates.
  3. (20 pts) Given that Find that
    iii
    $P(C\vert A)=?$. Are these two events ($A,C$) independent?
    iv
    $P(C\vert B)=?$. Are these two events ($B,C$) independent?
  4. (15 pts) The shelf life, in days, for bottles of a certain prescribed medicine is a random variable having the density function

    \begin{displaymath}
f(x)=\left\lbrace
\begin{array}{l}
\frac{20000}{(x+150)^3},~ x > 0 \\
0, ~elsewhere \\
\end{array}\right\rbrace
\end{displaymath}

    Find the probability that a bottle of this medicine will have a shell life of
    v
    at least 150 days;
    vi
    anywhere from 60 to 90 days.
  5. (15 pts) A private pilot wishes to insure his airplane for $200000. The insurance company estimates that a total loss may occur with probability 0.002, a 50% loss with probability 0.01, and a 25% loss with probability 0.1. Ignoring all other partial losses, what premium should the insurance company charge each year to realize an average profit of $500?

  6. (15 pts) Suppose that the probabilities are 0.4, 0.3, 0.2 and 0.1, respectively, that 0, 1, 2 and 3 power failures will strike a certain subdivision in any given year. Find the mean and variance of the random variable $X$ representing the number of power failures striking this subdivision.

  7. (20 pts) Compute $P(\mu - 2\sigma < X < \mu + 2\sigma)$, where $X$ has the density function

    \begin{displaymath}
f(x)=\left\lbrace
\begin{array}{l}
6x(1-x),~~ 0 < x < 1 \\
0,~~~~~~~~~~~~elsewhere\\
\end{array}\right.
\end{displaymath}

    and compare with the result given in Chebyshev's theorem.



Cem Ozdogan 2011-04-11