绘制具有置信区间的图

import numpy as np
import matplotlib.pyplot as plt
from scipy import stats

# 生成示例数据
np.random.seed(0)
data = np.random.normal(loc=5, scale=2, size=100)

# 计算均值和置信区间
mean = np.mean(data)
std_error = stats.sem(data)
confidence_interval = stats.t.interval(0.95, len(data)-1, loc=mean, scale=std_error)

# 绘制散点图和置信区间
plt.figure(figsize=(10, 6))
plt.scatter(np.arange(len(data)), data, label='Data Points')
plt.axhline(mean, color='red', linestyle='--', label='Mean')
plt.fill_between([0, len(data)-1], confidence_interval[0], confidence_interval[1], color='gray', alpha=0.5, label='95% Confidence Interval')

plt.xlabel('Index')
plt.ylabel('Value')
plt.title('Scatter Plot with 95% Confidence Interval')
plt.legend()
plt.show()