Exercise 2.3 Sales personnel for X Company are required to submit weekly reports
listing customer contacts made during the week. A sample of 61 weekly contact
reports showed a mean of 22.4 customer contacts per week for the sales personnel.
a)
The critical value for "\\alpha=0.05" and "df=n-1=61-1=60" degrees of freedom is "t_c= 2.000298."
The corresponding confidence interval is computed as shown below:
"=(22.4-2.000298\\times\\dfrac{ 5}{\\sqrt{61}}, 22.4+2.000298\\times\\dfrac{ 5}{\\sqrt{61}})"
"\\approx(21.11944, 23.68056)"
Therefore, based on the data provided, the 95% confidence interval for the population mean is "21.11944<\\mu<23.68056," which indicates that we are 95% confident that the true population mean "\\mu" is contained by the interval "(21.11944, 23.68056)."
b)
The critical value for "\\alpha=0.10" and "df=n-1=61-1=60" degrees of freedom is "t_c= 1.670649."
The corresponding confidence interval is computed as shown below:
"=(22.4-1.670649\\times\\dfrac{ 5}{\\sqrt{61}}, 22.4+1.670649\\times\\dfrac{ 5}{\\sqrt{61}})"
"\\approx(21.33048, 23.46952)"
Therefore, based on the data provided, the 90% confidence interval for the population mean is "21.33048<\\mu<23.46952," which indicates that we are 90% confident that the true population mean "\\mu" is contained by the interval "(21,33048, 23.46952)."
Level of significance is a statistical term for how willing you are to be wrong. With a 95 percent confidence interval, you have a 5 percent chance of being wrong. With a 90 percent confidence interval, you have a 10 percent chance of being wrong. A 99 percent confidence interval would be wider than a 95 percent confidence interval. A 90 percent confidence interval would be narrower.
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