Suppose the management claims that the proportion of games that your team wins when scoring 80 or more points is 0.50. 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 80 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 80 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_80_df = your_team_df[(your_team_df['pts'] > 80)] # Number of games won when your team scores over 80 points counts = (your_team_gt_80_df['game_result'] == 'W').sum() # Total number of games when your team scores over 80 points nobs = len(your_team_gt_80_df['game_result']) p = counts*1.0/nobs print("Proportion of games won by your team when scoring more than 80 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??) print("Hypothesis Test for the Population Proportion") print("Test Statistic =", round(test_statistic,2)) print("P-value =", round(p_value,4))
Suppose the management claims that the proportion of games that your team wins when scoring 80 or more points is 0.50. 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 80 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 80 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_80_df = your_team_df[(your_team_df['pts'] > 80)]
# Number of games won when your team scores over 80 points
counts = (your_team_gt_80_df['game_result'] == 'W').sum()
# Total number of games when your team scores over 80 points
nobs = len(your_team_gt_80_df['game_result'])
p = counts*1.0/nobs
print("Proportion of games won by your team when scoring more than 80 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??)
print("Hypothesis Test for the Population Proportion")
print("Test Statistic =", round(test_statistic,2))
print("P-value =", round(p_value,4))
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