3)
Assuming that the population of the study has a normal distribution and that you are studying the population mean μ.
The statistic hypotheses are

If you look at the alternative hypotheses, it includes the symbol "<", which indicates that the test is one-tailed. This means that you will reject the null hypotheses at small values of the test statistic.
Since the sample size is small (n=4) and the given sample data. The test statistic to use for the test is the Student's t:
![t=\frac{\bar{X}-\mu}{\frac{S}{\sqrt[]{n}}}\sim t_(n-1)](https://img.qammunity.org/2023/formulas/mathematics/college/y2q8widglmsl0rdwnrm69stjwlt2otx8ij.png)
To calculate the value of the statistic under the null hypothesis you have to use the sample data and the value of the population mean under the null hypothesis:
μ= 87.8
sample mean= 75
sample standard deviation= 17.1
n=4
![\begin{gathered} t_(H0)=\frac{75-87.8}{\frac{17.1}{\sqrt[]{4}}} \\ t_(H0)=(-12.8)/(8.55) \\ t_(H0)=-1.497 \end{gathered}](https://img.qammunity.org/2023/formulas/mathematics/college/ch0h5u2bw258vww9uj4ps9x07gpb0fmcyv.png)
The test statistic under the null hypothesis is -1.497
The p-value is the probability corresponding to the calculated statistic if possible under the null hypothesis.
So you have to calculate the probability of obtaining the value t=-1497
The student t has n-1 degrees of freedom, since the sample taken is n=4, the degree of freedom is 3.
The p-value is then the accumulated probability up to -1.497 under a t-distribution with 3 degrees of freedom:

The p-value is equal to 0.1157
4)
To make a decision using the p-value, you have to compare the said value with the level of significance, following the decision rule:
- If the p-value ≥ α, do not reject the null hypothesis.
- If the p-value < α, reject the null hypothesis.
The p-value (0.1157) is greater than the significance level (α= 0.05)
The decision is "do not reject the null hypothesis."