点估计的相对误差

Python 抽样

James Chapman

Curriculum Manager, DataCamp

样本量即行数

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

总体参数：

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

点估计：

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

相对误差（百分比）：

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：

相对误差与样本量的折线图。

Python 抽样