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    <title>统计学 on 老张开工了</title>
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    <description>Recent content in 统计学 on 老张开工了</description>
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      <title>统计学基础</title>
      <link>/posts/2025/01/statistics-basics/</link>
      <pubDate>Fri, 10 Jan 2025 00:00:00 +0000</pubDate>
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      <description>数据分析的第三只眼睛是统计学。没有统计学，你看到的只是数字的堆砌；有了统计学，你才能判断这些差异是否显著、这些趋势是否可靠。&#xA;本文的目标不是让你成为统计学家，而是让你掌握数据分析中最常用的统计工具——能看懂统计指标，能做假设检验，能判断什么时候该用什么方法。&#xA;环境准备 import numpy as np import pandas as pd import matplotlib.pyplot as plt import seaborn as sns from scipy import stats from scipy.stats import (norm, t, chi2, f, ttest_ind, ttest_rel, chisquare, f_oneway, pearsonr, spearmanr) import statsmodels.api as sm import warnings warnings.filterwarnings(&amp;#39;ignore&amp;#39;) plt.rcParams[&amp;#39;font.sans-serif&amp;#39;] = [&amp;#39;SimHei&amp;#39;] plt.rcParams[&amp;#39;axes.unicode_minus&amp;#39;] = False sns.set_theme(style=&amp;#39;whitegrid&amp;#39;) 描述性统计回顾 在动手之前，先快速温习基础篇学过的描述性统计。&#xA;data = np.random.normal(loc=50, scale=15, size=1000) # 集中趋势 mean = np.mean(data) median = np.median(data) mode = stats.mode(data, keepdims=True).mode[0] # 离散程度 variance = np.</description>
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