Answer to Question #94931 in Statistics and Probability for Marian

Question #94931
a statistics practitioner randomly sampled 100 observations from a population whose standard deviation is 5 and found that sample mean is 10. Estimate the population mean with 60% confidence.
b. Repeat part a with a sample size of 25
c. Repeat part a with a sample size of 10
d. describe what happens to the confidence interval estimate when the sample size decreases
1
Expert's answer
2019-09-23T09:34:26-0400

If we know the standard deviation of this population, the confidence interval for the mean can be found as


"(\\bar X - {q_{1 - \\frac{\\alpha }{2}}}\\frac{\\sigma }{{\\sqrt n }},\\bar X + {q_{1 - \\frac{\\alpha }{2}}}\\frac{\\sigma }{{\\sqrt n }})"

where "{\\bar X}" - sample mean, "n" - sample size, "\\sigma" - known standard deviation and "{q_{1 - \\frac{\\alpha }{2}}}" is quantile of the standard normal distribution of level "{1 - \\frac{\\alpha }{2}}" . Our significance level is

"\\alpha = 1 - \\frac{C}{{100\\% }} = 1 - \\frac{{60\\% }}{{100\\% }} = 0.4"

so we need to find "{q_{1 - \\frac{\\alpha }{2}}} = {q_{1 - \\frac{{0.4}}{2}}} = {q_{0.8}}" quantile. To do so use it's definition


"\\Phi ({q_y}) = y"

where "\\Phi (x)" is the CDF function of the standard normal distribution. Using the table of this CDF (I used the table from six-sigma-material.com)



We need to find a value of independent variable z such gives "0.8" as result. From the table we see, the value of z lies approximatelty at "z = 0.84" (for it "\\Phi (0.84) = 0.7995"). If we don't need high accuracy we don't use interpolation and just approximately accept


"{q_{0.8}} \\approx 0.84"


a) Using values we got above with "n=100"

"(\\bar X - {q_{1 - \\frac{\\alpha }{2}}}\\frac{\\sigma }{{\\sqrt n }},\\bar X + {q_{1 - \\frac{\\alpha }{2}}}\\frac{\\sigma }{{\\sqrt n }}) \\approx (10 - 0.84 \\cdot \\frac{5}{{\\sqrt {100} }},10 + 0.84 \\cdot \\frac{5}{{\\sqrt {100} }}) = (9.58,10.42)"

b) Do the same with "n=25"


"(\\bar X - {q_{1 - \\frac{\\alpha }{2}}}\\frac{\\sigma }{{\\sqrt n }},\\bar X + {q_{1 - \\frac{\\alpha }{2}}}\\frac{\\sigma }{{\\sqrt n }}) \\approx (10 - 0.84 \\cdot \\frac{5}{{\\sqrt {25} }},10 + 0.84 \\cdot \\frac{5}{{\\sqrt {25} }}) = (9.16,10.84)"

c) Do the same with "n=10"


"(\\bar X - {q_{1 - \\frac{\\alpha }{2}}}\\frac{\\sigma }{{\\sqrt n }},\\bar X + {q_{1 - \\frac{\\alpha }{2}}}\\frac{\\sigma }{{\\sqrt n }}) \\approx (10 - 0.84 \\cdot \\frac{5}{{\\sqrt {10} }},10 + 0.84 \\cdot \\frac{5}{{\\sqrt {10} }}) \\approx (8.67,11.33)"

d)Confidence interval for the mean is increasing with decreasing size of population.


P.S. Note that if we don't know standard deviation for population we need to use other method.


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