9.3: The Central Limit Theorem for Sample Proportions
- Page ID
- 105852
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\(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)If \(p\) is the proportion of a population that possesses a certain feature, then \(\hat{p}\), the proportion of a sufficiently large sample of size \(n\) that possess the same feature, is approximately normally distributed with the mean \(\mu_{\hat{p}}=p\) and the standard deviation \(\sigma_{\hat{p}}=\sqrt{\dfrac{p(1-p)}{n}}\). In this context, a "large" sample is such that \(np\geq10\) and \(n(1-p)\geq10\).
Symbolically, the statement can be written in the following way:
For \(X\sim?(p)\), when \(np\geq10\) and \(n(1-p)\geq10\),
\(\hat{p}\sim N\left(\mu_{\hat{p}}=p, \sigma_{\hat{p}}=\sqrt{\dfrac{p(1-p)}{n}}\right)\)
According to a study, 5.4% of the passengers fly first-class. A random sample of size 215 was obtained by a researcher. Find the probability that at least 10 people in the sample are first-class passengers.
Solution
Let \(p\) be the proportion of people that fly first-class, then \(p=0.054\).
Let \(\hat{p}\) be the proportion of people that fly first-class in the sample of 215 random passengers. Since the sample is large, i.e.
\(np=215\cdot0.054=11.61\geq10\) and \(n(1-p)=215\cdot(1-0.054)=215\cdot0.946=203.39\geq10\)
by CLT,
\(\hat{p}\sim N\left(\mu_{\hat{p}}=p=0.054, \sigma_{\hat{p}}=\sqrt{\dfrac{p(1-p)}{n}}=\sqrt{\dfrac{0.054(1-0.054)}{215}}=0.0154\right)\)
Then the probability that at least 10 people (i.e., proportion is at least 10/215) in the sample are first-class passengers can be expressed as
\(P(\hat{p}>\frac{10}{215})=P(\hat{p}>0.0465)=P\left(\dfrac{\hat{p}-\mu_{\hat{p}}}{\sigma_{\hat{p}}}>\dfrac{0.0465-0.054}{0.0154}\right)=P(Z>-0.49)=0.6879=68.79\%\)
Or using technology,
\(P(\hat{p}>0.0465)=0.6869=68.69\%\)


