Question

How can I do these operations in python ?

Given a loaded dataset:

a) At the α = 0.05 significance level, test whether the variance of rental prices differs

for private room rentals compared to entire house rentals.

b) At the α = 0.01 significance level, test whether the average price of entire house

rentals is greater than the average price of private room rentals.

Answer 1

Sample dataset

Part a

Part b

Python code in text

import pandas as pd
data = [['House', 20000], ['House', 25000], ['House', 22000],['Private', 5000], ['Private', 7000], ['Private', 9000]]
df = pd.DataFrame(data, columns = ['accommodation', 'Price'])
print(df)

from scipy import stats
import matplotlib.pyplot as plt
ret=stats.f_oneway(df["Price"][df["accommodation"]=="House"],df["Price"][df["accommodation"]=="Private"])
print(ret)
if ret[1]<0.05:

print("Reject the null hypothesis so accommodation types have differences in variances")

else:

print("Accept the null hypothesis so accommodation types have similar variances")

df.boxplot("Price",by="accommodation")
plt.show()

Private=df[df["accommodation"]=="Private"]
entirehouse=df[df["accommodation"]=="House"]
ret=stats.ttest_ind(Private["Price"],entirehouse["Price"])
if ret[1]<0.05:

print("Reject the null hypothesis so average price of entire house is greater")

else:

print("Accept the null hypotheses so average price of entire house isn't greater")