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so if y = 2, then 2y = 4, thus
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Answer:
The upper confidence bound for population mean escape time is: 379.27
The upper prediction bound for the escape time of a single additional worker is 413.64
Step-by-step explanation:
Given that :
sample size n = 26
sample mean = 371.08
standard deviation = 24.45
The objective is to calculate an upper confidence bound for population mean escape time using a confidence level of 95%
We need to determine the standard error of these given data first;
So,
Standard Error S.E =
Standard Error S.E =
Standard Error S.E =
Standard Error S.E = 4.7950
However;
Degree of freedom df= n - 1
Degree of freedom df= 26 - 1
Degree of freedom df= 25
At confidence level of 95% and Degree of freedom df of 25 ;
t-value = 1.7080
Similarly;
The Margin of error = t-value × S.E
The Margin of error = 1.7080 × 4.7950
The Margin of error = 8.18986
The upper confidence bound for population mean escape time is = Sample Mean + Margin of Error
The upper confidence bound for population mean escape time is = 371.08 + 8.18986
The upper confidence bound for population mean escape time is = 379.26986 379.27
The upper confidence bound for population mean escape time is: 379.27
b. Calculate an upper prediction bound for the escape time of a single additional worker using a prediction level of 95%.
The standard error of the mean =
The standard error of the mean =
The standard error of the mean =
The standard error of the mean =
The standard error of the mean =
The standard error of the mean = 24.91575614
Recall that : At confidence level of 95% and Degree of freedom df of 25 ;
t-value = 1.7080
∴
The Margin of error = t-value × S.E
The Margin of error = 1.7080 × 24.91575614
The Margin of error = 42.55611149
The upper prediction bound for the escape time of a single additional worker is calculate by the addition of
Sample Mean + Margin of Error
= 371.08 + 42.55611149
= 413.6361115
413.64
The upper prediction bound for the escape time of a single additional worker is 413.64