First let us determine the null and alternate hypothesis:
Null hypothesis states that the mean work week length is \(60\) hours and the alternate hypothesis states that the mean work week length is less than \(60\) hours.
\(H_{0}:\mu \geq 60\)
\(H_{a}:\mu < 60\)
Here the random variable which is \(\bar{X}\), the mean length of the work week. Since we do not know the population standard deviation we use student’s t-distribution for this test.
\(t_{n-1}=t_{10-1}\)
\(t_{9}\)
Thus, the t test statistic is calculated using the following formula:
\(t=\frac{\bar{X}-\mu}{s/\sqrt{n}}\)
Here \(\bar{X}\) is the sample mean and µ is the population mean, \(s\) is the standard deviation and n is the sample size. Now let’s calculate the sample mean using the data given in the question:
\(\bar{X}=\frac{70+45+55+60+65+55+55+60+50+55}{10}\)
\(=\frac{570}{10}\)
\(=57\)
Therefore let us calculate \(z\) value using the formula-
\(z=\frac{\bar{X}-\mu}{\sigma/\sqrt{n}}\)
\(=\frac{57-60}{7.15/\sqrt{10}}\)
\(=\frac{-3}{7.15/3.162}\)
\(=\frac{-3}{2.26}\)
\(=-1.327\)
After this step let us find the \(r-\)value using NORMSDIST function in excel.

Thus the following is the student’s \(t-\)distribution curve for the hypothesis test.

We know that alpha value is \(0.05\) and the \(p-\)value is greater than the alpha value therefore the null hypothesis is not rejected. Since null hypothesis is not rejected we do not have enough evidence to state that that the the mean work week length is less than \(60\) hours.
Now let us determine the \(95%\) confidence interval:
Thus the \(95%\) confidence level indicates that the mean work week length lies within \(52.57\) and \(109.57\). Let us represent the same in the student’s t-distribution curve
