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Suppose that n students are selected at random without replacement from a class containing T students, of whom A are boys and T – A are girls. Let X denote the number of boys that are obtained. For what sample size n will Var(X) be a maximum?

Short Answer

Expert verified

Thevalue of n for which the value of Var(X) will be a maximum is:

\[\begin{array}{l}\frac{{T - 1}}{2}\;or\;\frac{{T + 1}}{2}\;if\;T\;is\;odd\\\frac{T}{2}\;if\;T\;is\;even\end{array}\]

Step by step solution

01

Given information

Let X is a random variable that follows Hypergeometric distribution with parameters A,B and n. Here, the parameter values are A = A, B = T-A, and n=n that is, \[X \sim Hyp\left( {A,T - A,n} \right)\].

02

Variance formula and substituting the values 

From theorem 5.3.4 in the textbook, if X is a hypergeometric variable, then the variance of X is

\(Var\left( X \right) = \frac{{nAB}}{{{{\left( {A + B} \right)}^2}}} \cdot \frac{{A + B - n}}{{A + B - 1}}\)

On substituting the values,

\[\begin{array}{c}Var\left( X \right) = \frac{{n\; \cdot A \cdot \left( {T - A} \right)}}{{{{\left( {A + T - A} \right)}^2}}} \cdot \frac{{\left( {A + T - A} \right) - n}}{{\left( {A + T - A} \right) - 1}}\\ = \frac{{n \cdot A \cdot \left( {T - A} \right)}}{{{T^2}}} \cdot \frac{{T - n}}{{T - 1}}\\ = \frac{1}{{{T^2} \cdot \left( {T - 1} \right)}}\left[ {nA{T^2} - {n^2}AT - n{A^2}T + {n^2}{A^2}} \right] \ldots \left( 1 \right)\end{array}\]

03

Finding the desirable value of n

In order to find the value of n for which the value of Var(X) will be a maximum, one need to differentiate the above equation \(\left( 1 \right)\) with respect to n.

\(\frac{{\partial Var\left( X \right)}}{{\partial X}} = \frac{1}{{{T^2} \cdot \left( {T - 1} \right)}}\left[ {A{T^2} - 2nAT - {A^2}T + 2n{A^2}} \right] \ldots \left( 2 \right)\)

Equating \(\left( 2 \right)\) with 0

\(\)

\(\begin{array}{c}\frac{1}{{{T^2} \cdot \left( {T - 1} \right)}}\left[ {A{T^2} - 2nAT - {A^2}T + 2n{A^2}} \right] = 0\\2n\left( {A - T} \right) = T\left( {A - T} \right)\\n = \frac{T}{2}\end{array}\)

But, if T is not an even number, the value of n won’t be an integer. Therefore, we can either use \[\frac{{T - 1}}{2}\;or\;\frac{{T + 1}}{2}\]if T is odd.

Therefore, the answer is:

\[\begin{array}{l}\frac{{T - 1}}{2}\;or\;\frac{{T + 1}}{2}\;if\;T\;is\;odd\\\frac{T}{2}\;if\;T\;is\;even\end{array}\].

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Most popular questions from this chapter

Suppose that 16 percent of the students in a certain high school are freshmen, 14 percent are sophomores, 38 percent are juniors, and 32 percent are seniors. If 15 students are selected at random from the school, what is the

The probability that at least eight will be either freshmen or sophomores?

If a random sample of 25 observations is taken from the normal distribution with mean \(\mu \) and standard deviation 2, what is the probability that the sample mean will lie within one unit of μ ?

Suppose that F is a continuous c.d.f. on the real line, and let \({{\bf{\alpha }}_{\bf{1}}}\,{\bf{and}}\,{{\bf{\alpha }}_{\bf{2}}}\)be numbers such that \({\bf{F}}\left( {{{\bf{\alpha }}_{\bf{1}}}} \right)\,{\bf{ = 0}}{\bf{.3}}\,{\bf{and}}\,{\bf{F}}\left( {\,{{\bf{\alpha }}_{\bf{2}}}} \right){\bf{ = 0}}{\bf{.8}}{\bf{.}}\). Suppose 25 observations are selected at random from the distribution for which the c.d.f. is F. What is the probability that six of the observed values will be less than \({{\bf{\alpha }}_{\bf{1}}}\), 10 of the observed values will be between \({{\bf{\alpha }}_{\bf{1}}}\) and \({{\bf{\alpha }}_{\bf{2}}}\), and nine of the observed values will be greater than \({{\bf{\alpha }}_{\bf{2}}}\)?

Suppose that a machine produces parts that are defective with probability P, but P is unknown. Suppose that P has a continuous distribution with pdf.

\({\bf{f}}\left( {\bf{p}} \right){\bf{ = }}\left\{ \begin{array}{l}{\bf{10}}{\left( {{\bf{1 - p}}} \right)^{\bf{9}}}\;\;{\bf{if}}\,{\bf{0 < p < 1,}}\\{\bf{0}}\;\;{\bf{otherwise}}{\bf{.}}\end{array} \right.\).

Conditional on\(P = p\), assume that all parts are independent of each other. Let X be the number of non defective parts observed until the first defective part. If we observe X = 12, compute the conditional pdf. of P given X = 12.

It is said that a random variable X has the Pareto distribution with parameters\({{\bf{x}}_{\bf{0}}}\,{\bf{and}}\,{\bf{\alpha }}\) if X has a continuous distribution for which the pdf\({\bf{f}}\left( {{\bf{x|}}\,{{\bf{x}}_{\bf{0}}}{\bf{,\alpha }}} \right)\) is as follows

\(\begin{array}{l}{\bf{f}}\left( {{\bf{x|}}\,{{\bf{x}}_{\bf{0}}}{\bf{,\alpha }}} \right){\bf{ = }}\frac{{{\bf{\alpha }}{{\bf{x}}_{\bf{0}}}^{\bf{\alpha }}}}{{{{\bf{x}}^{{\bf{\alpha + 1}}}}}}\,{\bf{,x}} \ge {{\bf{x}}_{\bf{0}}}\\\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,{\bf{ = }}\,{\bf{0}}\,\,{\bf{,x < }}{{\bf{x}}_{\bf{0}}}\end{array}\)

Show that if X has this Pareto distribution, then the random variable\({\bf{log}}\left( {{\bf{X|}}\,{{\bf{x}}_{\bf{0}}}} \right)\)has the exponential distribution with parameter α.

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