Chapter 4: Problem 20
When 100 tacks were thrown on a table, 60 of them landed point up. Obtain a \(95 \%\) confidence interval for the probability that a tack of this type lands point up. Assume independence.
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Chapter 4: Problem 20
When 100 tacks were thrown on a table, 60 of them landed point up. Obtain a \(95 \%\) confidence interval for the probability that a tack of this type lands point up. Assume independence.
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A number is to be selected from the interval \(\\{x: 0
Two different teaching procedures were used on two different groups of students. Each group contained 100 students of about the same ability. At the end of the term, an evaluating team assigned a letter grade to each student. The results were tabulated as follows. \begin{tabular}{ccccccc} \hline & \multicolumn{5}{c} { Grade } & \\ \cline { 2 - 6 } Group & A & B & C & D & F & Total \\ \hline I & 15 & 25 & 32 & 17 & 11 & 100 \\ II & 9 & 18 & 29 & 28 & 16 & 100 \\ \hline \end{tabular} If we consider these data to be independent observations from two respective multinomial distributions with \(k=5\), test at the \(5 \%\) significance level the hypothesis that the two distributions are the same (and hence the two teaching procedures are equally effective).
In the Program Evaluation and Review Technique (PERT), we are interested in
the total time to complete a project that is comprised of a large number of
subprojects. For illustration, let \(X_{1}, X_{2}, X_{3}\) be three independent
random times for three subprojects. If these subprojects are in series (the
first one must be completed before the second starts, etc.), then we are
interested in the sum \(Y=X_{1}+X_{2}+X_{3}\). If these are in parallel (can be
worked on simultaneously), then we are interested in \(Z=\max \left(X_{1},
X_{2}, X_{3}\right) .\) In the case each of these random variables has the
uniform distribution with pdf \(f(x)=1,0
Let the joint pdf of \(X\) and \(Y\) be \(f(x, y)=\frac{12}{7} x(x+y),
0
Let \(z^{*}\) be drawn at random from the discrete distribution which has mass \(n^{-1}\) at each point \(z_{i}=x_{i}-\bar{x}+\mu_{0}\), where \(\left(x_{1}, x_{2}, \ldots, x_{n}\right)\) is the realization of a random sample. Determine \(E\left(z^{*}\right)\) and \(V\left(z^{*}\right)\).
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