Step 5: Hypothesis Test for the Population Proportion

Suppose the management claims that the proportion of games that your team wins when scoring 102 or more points is 0.90. Test this claim using a 5% level of significance. Make the following edits to the code block below:

Replace??COUNT_VAR??with the variable name that represents the number of games won when your team scores over 102 points.(Hint: this variable is in the code block below).

Replace??NOBS_VAR??with the variable name that represents the total number of games when your team scores over 102 points.(Hint: this variable is in the code block below).

Replace??NULL_HYPOTHESIS_VALUE??with the proportion under the null hypothesis.

from statsmodels.stats.proportion import proportions_ztest

your_team_gt_102_df = your_team_df[(your_team_df['pts'] > 102)]

# Number of games won when your team scores over 102 points counts = (your_team_gt_102_df['game_result'] == 'W').sum()

# Total number of games when your team scores over 102 points nobs = len(your_team_gt_102_df['game_result'])

p = counts*1.0/nobs print("Proportion of games won by your team when scoring more than 102 points in the years 2013 to 2015 =", round(p,4))

# Hypothesis Test # ---- TODO: make your edits here ---- test_statistic, p_value = proportions_ztest(??COUNT_VAR??, ??NOBS_VAR??, ??NULL_HYPOTHESIS_VALUE??, prop_var=??NULL_HYPOTHESIS_VALUE??)

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