Answer to Question #335711 in Statistics and Probability for Junior

Question #335711

The following are the ages of 8 jeepney passengers in a waiting shed: 12, 15, 18, 19, 21, 23, 35, and 40. The sample with size 7 is chosen to ride in the current jeepney. Determine the number of possible samples with size 7


1
Expert's answer
2022-05-02T16:23:44-0400

We have population values 12, 15, 18, 19, 21, 23, 35, and 40 population size N=8 and sample size n=7.

Mean of population "(\\mu)" = 

"\\dfrac{12+15+18+19+21+23+35+40}{8}=22.875"


Variance of population 


"\\sigma^2=\\dfrac{\\Sigma(x_i-\\bar{x})^2}{n}=82.859375"


"\\sigma=\\sqrt{\\sigma^2}=\\sqrt{6}"

The number of possible samples which can be drawn without replacement is "^{N}C_n=^{8}C_7=8."

"\\def\\arraystretch{1.5}\n \\begin{array}{c:c:c:c:c}\n no & Sample & Sample \\\\\n& & mean\\ (\\bar{x})\n\\\\ \\hline\n 1 & 12, 15, 18, 19, 21, 23, 35 & 143\/7 \\\\\n \\hdashline\n 2 & 12, 15, 18, 19, 21, 23, 40 & 148\/7 \\\\\n \\hdashline\n 3 & 12, 18, 19, 21, 23, 35,40 & 168\/7 \\\\\n \\hdashline\n 4 & 12, 15, 19, 21, 23, 35, 40 & 165\/7 \\\\\n \\hdashline\n 5 & 12, 15, 18, 21, 23, 35, 40 & 164\/7 \\\\\n \\hdashline\n 6 & 12, 15,18, 19, 23, 35,40 & 162\/7 \\\\\n \\hdashline\n 7 & 12,15, 18, 19, 21, 35,40 & 160\/7 \\\\\n \\hdashline\n 8 & 15, 18, 19, 21, 23, 35, 40 & 171\/7 \\\\\n \\hdashline\n\\end{array}"




"\\def\\arraystretch{1.5}\n \\begin{array}{c:c:c:c:c}\n \\bar{X} & f(\\bar{X}) &\\bar{X} f(\\bar{X}) &\\bar{X}^2 f(\\bar{X})\\\\ \\hline\n 143\/7 & 1\/8 & 143\/56 & 20449\/392\\\\\n \\hdashline\n 148\/7 & 1\/8 & 148\/56 & 21904\/392\\\\\n \\hdashline\n 168\/7 & 1\/8 & 168\/56 & 28224\/392\\\\\n \\hdashline\n 165\/7 & 1\/8 & 165\/56 & 27225\/392 \\\\\n \\hdashline\n 164\/7 & 1\/8 & 164\/56 & 26896\/392\\\\\n \\hdashline\n 162\/7 & 1\/8 & 162\/56 & 26244\/392 \\\\\n \\hdashline\n 160\/7 & 1\/8 & 160\/56 & 25600\/392 \\\\\n \\hdashline\n 171\/7 & 1\/8 & 171\/56 & 29241\/392 \\\\\n \\hdashline\n\\end{array}"


Mean of sampling distribution 

"\\mu_{\\bar{X}}=E(\\bar{X})=\\sum\\bar{X}_if(\\bar{X}_i)=22.875=\\mu"


The variance of sampling distribution 

"Var(\\bar{X})=\\sigma^2_{\\bar{X}}=\\sum\\bar{X}_i^2f(\\bar{X}_i)-\\big[\\sum\\bar{X}_if(\\bar{X}_i)\\big]^2""=\\dfrac{205783}{392}-(\\dfrac{183}{8})^2=\\dfrac{5303}{3136}= \\dfrac{\\sigma^2}{n}(\\dfrac{N-n}{N-1})"

"\\sigma_{\\bar{X}}=\\sqrt{\\dfrac{5303}{3136}}\\approx1.3004"


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