Answer to Question #255196 in Statistics and Probability for Thafeng

Question #255196

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?                   


1
Expert's answer
2021-10-25T14:44:15-0400

(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:


"CI=(\\bar{X}-t_c\\times\\dfrac{s}{\\sqrt{n}}, \\bar{X}+t_c\\times\\dfrac{s}{\\sqrt{n}})"

"=(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:


"CI=(\\bar{X}-t_c\\times\\dfrac{s}{\\sqrt{n}}, \\bar{X}+t_c\\times\\dfrac{s}{\\sqrt{n}})"

"=(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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