Fondamenti dell'inferenza in Python
Paul Savala
Assistant Professor or Mathematics

investments_df.groupby('market')['funding_total_usd'].mean()
Market Average funding
=========== ===============
Advertising 13806610
Analytics 14762930
Biotechnology 20838670
... ...
health_df = investments_df[investments_df['market'] == 'Health and Wellness']
health_df['funding_total_usd'].plot(kind='hist')

health_log = np.log(health_df['funding_total_usd'])health_log.plot(kind='hist')

investments_df['log_funding'] = np.log(investments_df['funding_total_usd'])investments_df.groupby('market')['log_funding'].std()
Advertising 2.254390
Analytics 2.152852
Biotechnology 1.946059
... ...
Test di Levene per varianze uguali
$H_0:$ Le popolazioni hanno varianze uguali
$H_a:$ Le popolazioni hanno varianze diverse
from scipy import stats health_df = investments_df[investments_df['market'] == 'Health and Wellness'] analytics_df = investments_df[investments_df['market'] == 'Analytics']s, p_value = stats.levene(health_df['log_funding'], analytics_df['log_funding'])print(p_value < 0.05)
False
Conclusione: Non si rifiuta l'ipotesi nulla. I mercati hanno varianza di funding uguale.
s, p_value = stats.f_oneway(health_df['log_funding'], analytics_df['log_funding'])print(p_value < 0.05)
True
Conclusione: I mercati hanno funding significativamente diverso.
Fondamenti dell'inferenza in Python