Choosing the Criterion
The preprocessed file is already put in the code editor!
As we did with the first A/B test, we will do it now. We need to:
Look at the distribution of the data;
Choosing the table below decide what criterion to select for the work.
Завдання
Swipe to start coding
- Import the
seabornwith thesnsalias. - Import the
scipy. - Import the
statsmodels.apiwith thesmalias. - Build the
distplotusing thesnslibrary and the'contact_views_number'column. - Build the
qqplotusing thesmlibrary and the'contact_views_number'column. - Perform the
normaltestwith the'contact_views_number'column.
Рішення
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# Importing the pandas
import pandas as pd
# Import the seaborn
import seaborn as sns
# Import the scipy
import scipy
# Import the statsmodels.api
import statsmodels.api as sm
# Reading the file
df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/1e089012-bfcf-4d61-9ac9-bb649ece39f2/abtest_with_changes.csv')
# Build the distplot
sns.distplot(df.contact_views_number)
# Build the qqplot
sm.qqplot(df.contact_views_number, line = 's')
# Perform the normaltest
print(scipy.stats.normaltest(df.contact_views_number))
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Секція 3. Розділ 4
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# Importing the pandas
import pandas as pd
# Import the seaborn
import ___ as sns
# Import the scipy
import ___
# Import the statsmodels.api
import ___.api as ___
# Reading the file
df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/1e089012-bfcf-4d61-9ac9-bb649ece39f2/abtest_with_changes.csv')
# Build the distplot
sns.___(df.___)
# Build the qqplot
sm.___(___.___, line = 's')
# Perform the normaltest
print(scipy.stats.___(df.___))
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