Perform a hypothesis test to test whether average weekly time spent on the study plan is less than 150 minutes per week

Perform a hypothesis test to test whether average weekly time spent on the study plan is less than 150 minutes per week. Use an α=0.05.
a.)    Write the hypotheses in symbol notation.

b.)    Paste the output for the hypothesis test from Stat Crunch below.  Circle the p-value.

Perform a hypothesis test to test whether average weekly time spent on the study plan is less than 150 minutes per week

This problem set uses the same dataset as before, MSLGrades.xls,  with the student information.   We will use Statcrunch  to perform all statistical analyses on the dataset.  Open the MSLGrades.xls dataset in Statcrunch.   Copy and paste all output into the document.  Make sure to answer all questions fully.

At the beginning of the semester, it is suggested that you spend 30 minutes per day on your study plan or 150 minutes per week.

1.)    Perform a hypothesis test to test whether average weekly time spent on the study plan is less than 150 minutes per week. Use an α=0.05.

a.)    Write the hypotheses in symbol notation.

b.)    Paste the output for the hypothesis test from Stat Crunch below.  Circle the p-value.

c.)     Write the probability statement for your p-value with the correct.

d.)    Make your decision.

e.)    Draw conclusions.

2.)    Looking at the sample mean, is there practical significance? Write a sentence explaining your results as if you were explaining to a peer.
More details;

Hypothesis Testing

In everyday life, we often have to make decisions based on incomplete information. These may be decisions that are
important to us such as, “Will I improve my biology grades if I spend more time studying vocabulary?” or “Should
I become a chemistry major to increase my chances of getting into med school?” This section is about the use of
hypothesis testing to help us with these decisions. Hypothesis testing is a kind of statistical inference that involves
asking a question, collecting data, and then examining what the data tells us about how to procede.