a) A random sample of employee files is drawn revealing an average of 2.8 overtime hours worked per week with a standard deviation of 0.7. The sample size is 500.
(i) What is the standard error of the mean based on this information? (2)
(ii) What is the 98% confidence interval for the number of overtime hours worked? (5)
How would your result be affected if the sample size had been 100?
(i)
"SE=\\dfrac{s}{\\sqrt{n}}=\\dfrac{0.7}{\\sqrt{500}}\\approx0.031305"(ii) The critical value for "\\alpha = 0.02" and "df = n-1 = 500-1=499" degrees of freedom is "t_c = z_{1-\\alpha\/2; n-1} = 2.333844." The corresponding confidence interval is computed as shown below:
"=(2.8-2.333844\\times\\dfrac{0.7}{\\sqrt{500}}, 2.8+2.333844\\times\\dfrac{0.7}{\\sqrt{500}})"
"=(2.727, 2.873)"
Therefore, based on the data provided, the 98% confidence interval for the population mean is "2.727 < \\mu < 2.873," which indicates that we are 98% confident that the true population mean "\\mu" is contained by the interval "(2.727, 2.873)"
(iii) The critical value for "\\alpha = 0.02" and "df = n-1 = 100-1=99" degrees of freedom is "t_c = z_{1-\\alpha\/2; n-1} = 2.364606." The corresponding confidence interval is computed as shown below:
"=(2.8-2.364606\\times\\dfrac{0.7}{\\sqrt{100}}, 2.8+2.364606\\times\\dfrac{0.7}{\\sqrt{100}})"
"=(2.6345, 2.9655)"
Therefore, based on the data provided, the 98% confidence interval for the population mean is "2.6345 < \\mu < 2.9655," which indicates that we are 98% confident that the true population mean "\\mu" is contained by the interval "(2.6345, 2.9655)"
Decreasing the sample size causes the error bound to increase, making the confidence interval wider.
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