Step 4: Hypothesis Test for the Population Mean (II)

A team averaging 110 points is likely to do very well during the regular season. The coach of your team has hypothesized that your team scored at an average of less than 110 points in the years 2013-2015. Test this claim at a 1% level of significance. For this test, assume that the population standard deviation for relative skill level is unknown.

1. The dataframe for your team is called your_team_df.
2. The variable 'pts' represents the points scored by your team.
3. Calculate and print the mean points scored by your team during the years you picked.
4. Identify the mean score under the null hypothesis. You only have to identify this value and do not have to print it. (Hint: this is given in the problem statement)
5. Assuming that the population standard deviation is unknown, use Python methods to carry out the hypothesis test.
6. Calculate and print the test statistic rounded to two decimal places.
7. Calculate and print the P-value rounded to four decimal places.

Here is data from previous steps

import scipy.stats as st

# Mean relative skill level of your team mean_elo_your_team = your_team_df['elo_n'].mean() print("Mean Relative Skill of your team in the years 2013 to 2015 =", round(mean_elo_your_team,2))

# Hypothesis Test # ---- TODO: make your edits here ---- test_statistic, p_value = st.ttest_1samp(your_team_df['elo_n'], 1420)

print("Hypothesis Test for the Population Mean") print("Test Statistic =", round(test_statistic,2)) print("P-value =", round(p_value,4))

Mean Relative Skill of your team in the years 2013 to 2015 = 1440.49 Hypothesis Test for the Population Mean Test Statistic = 4.04 P-value = 0.0001