import matplotlib
from datascience import *
%matplotlib inline
import matplotlib.pyplot as plots
import numpy as np
plots.style.use('fivethirtyeight')
# Population of size 10
ones = 5
zero_one_population = np.append(np.ones(ones), np.zeros(10 - ones))
zero_one_population
np.mean(zero_one_population), np.std(zero_one_population)
pop_proportions = make_array()
pop_SDs = make_array()
for k in np.arange(1, 10):
population = np.append(np.ones(k), np.zeros(10 - k))
population_SD = np.std(population)
pop_SDs = np.append(pop_SDs, population_SD)
pop_proportions = np.append(pop_proportions, k/10)
sd_table = Table().with_columns(
'Population Proportion', pop_proportions,
'Population SD', pop_SDs
)
sd_table
sd_table.scatter(0)