点推定の相対誤差

Pythonで学ぶサンプリング

James Chapman

Curriculum Manager, DataCamp

標本サイズは行数

len(coffee_ratings.sample(n=300))

len(coffee_ratings.sample(frac=0.25))

coffee_ratings['total_cup_points'].mean()

82.15120328849028

coffee_ratings.sample(n=10)['total_cup_points'].mean()

83.027

coffee_ratings.sample(n=100)['total_cup_points'].mean()

82.4897

coffee_ratings.sample(n=1000)['total_cup_points'].mean()

82.1186

母集団パラメータ:

population_mean = coffee_ratings['total_cup_points'].mean()

点推定:

sample_mean = coffee_ratings.sample(n=sample_size)['total_cup_points'].mean()

相対誤差（%）:

rel_error_pct = 100 * abs(population_mean-sample_mean) / population_mean

import matplotlib.pyplot as plt
errors.plot(x="sample_size", 
            y="relative_error", 
            kind="line")
plt.show()

特性:

相対誤差と標本サイズの折れ線グラフ。

Pythonで学ぶサンプリング