01 Introduction to sampling distributions#

%%html
<iframe width="700" height="400" src="https://www.youtube.com/embed/z0Ry_3_qhDw/" frameborder="0" allowfullscreen></iframe>

import itertools
import numpy as np
import pandas as pd
from pandas import Series, DataFrame
import matplotlib.pyplot as plt
import seaborn as sns
from scipy import stats, special

khanacademy

Introduction to sampling distributions fig 1

df = DataFrame({"#'s picks": list(itertools.product([1, 2, 3], repeat=2))})

df['X'] = [np.mean(i) for i in df["#'s picks"]]

df
#'s picks X
0 (1, 1) 1.0
1 (1, 2) 1.5
2 (1, 3) 2.0
3 (2, 1) 1.5
4 (2, 2) 2.0
5 (2, 3) 2.5
6 (3, 1) 2.0
7 (3, 2) 2.5
8 (3, 3) 3.0 
df['X'].plot(kind='hist',
             bins=np.arange(0.5, 4, 0.5),
             width=0.02)

<AxesSubplot:ylabel='Frequency'>
../_images/01 Introduction to sampling distributions_8_1.png 
# np.random.sample, random.sample