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Jingdong book

统计思维：程序员数学之概率统计（第2版）

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Jingdong book

统计思维：程序员数学之概率统计（第2版）

Name: 统计思维：程序员数学之概率统计（第2版）
Brand: Jingdong book
SKU: 3118160831
Price: 32.88 USD
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Editer Recommend

现实工作中，人们常常需要用数据说话。可是，数据自己不会说话，需要人对它进行分析和挖掘才能找到有价值的信息。概率统计是数据分析的通用语言，是大数据时代预测未来的根基。如果你有编程背景，就能以概率和统计学为工具，将数据转化为有用的信息和知识，让数据说话。本书介绍了如何借助计算而非数学方法，使用Python语言对数据进行统计分析。

通过书中有趣的案例，你可以学到探索性数据分析的整个过程，从数据收集和生成统计量，到发现模式和检验假设。你还将探索概率分布、概率法则、可视化技术，以及其他许多工具和概念。

这一版内容较第1版有很多改动，并且新增了回归、时间序列分析、生存分析和分析方法章节，以丰富你的知识。

通过学习本书，你将能够：

编写测试代码深入理解概率论和统计学；
运行实验检验统计行为特征，如生成服从各种分布的样本；
通过模拟理解数学上艰涩的概念；
学习贝叶斯估计等实用内容；
用Python从大部分数据源导入数据，不依赖由统计工具清洗的格式化数据；
用统计推理解读现实世界中的数据。

Content Description

《统计思维：程序员数学之概率统计（第2版）》是一本以全新视角讲解概率统计的入门图书。抛开经典的数学分析，Downey手把手教你用编程理解统计学。
具体说来，《统计思维：程序员数学之概率统计（第2版）》通过一个案例研究，介绍探索性数据分析的全过程：从收集数据、生成统计信息，到发现模式、验证假设。同时研究分布、概率规则、可视化和其他多种工具及概念。此外，第2版新增了回归、时间序列分析、生存分析和分析方法等章节。

Author Description

Allen B. Downey是富兰克林欧林工程学院计算机科学教授，曾执教于韦尔斯利学院、科尔比学院和加州大学伯克利分校。在加州大学伯克利分校获得计算机科学博士学位。Downey已出版十余本技术书，包括Think Python、Think Bayes、Think Complexity等。

Catalogue

前言 xi
第1章探索性数据分析1
1．1统计学方法2
1．2全国家庭增长调查2
1．3数据导入3
1．4DataFrame4
1．5变量6
1．6数据变换6
1．7数据验证8
1．8解释数据9
1．9练习10
1．10术语11
第2章分布13
2．1表示直方图14
2．2绘制直方图14
2．3全国家庭增长调查中的变量15
2．4离群值18
2．5第一胎18
2．6分布概述20
2．7方差21
2．8效应量21
2．9报告结果22
2．10练习23
2．11术语23
第3章概率质量函数25
3．1概率质量函数25
3．2绘制PMF26
3．3绘制PMF 的其他方法28
3．4课堂规模悖论29
3．5使用DataFrame 进行索引31
3．6练习33
3．7术语34
第4章累积分布函数35
4．1PMF 的局限35
4．2百分位数36
4．3CDF37
4．4表示CDF38
4．5比较CDF39
4．6基于百分位数的统计量40
4．7随机数41
4．8比较百分位秩42
4．9练习43
4．10术语44
第5章分布建模45
5．1指数分布45
5．2正态分布48
5．3正态概率图49
5．4对数正态分布51
5．5Pareto 分布53
5．6随机数生成56
5．7为什么使用模型56
5．8练习57
5．9术语59
第6章概率密度函数61
6．1PDF61
6．2核密度估计63
6．3分布框架65
6．4Hist 实现65
6．5Pmf 实现66
6．6Cdf 实现67
6．7矩68
6．8偏度69
6．9练习72
6．10术语73
第7章变量之间的关系75
7．1散点图75
7．2描述关系特征78
7．3相关性79
7．4协方差80
7．5Pearson 相关性81
7．6非线性关系82
7．7Spearman 秩相关82
7．8相关性和因果关系83
7．9练习84
7．10术语85
第8章估计87
8．1估计游戏87
8．2猜测方差89
8．3抽样分布90
8．4抽样偏倚93
8．5指数分布93
8．6练习95
8．7术语95
第9章假设检验97
9．1经典假设检验97
9．2假设检验98
9．3检验均值差100
9．4其他检验统计量101
9．5检验相关性102
9．6检验比例103
9．7卡方检验104
9．8再谈第一胎105
9．9误差106
9．10功效107
9．11复现108
9．12练习109
9．13术语109
第10章线性最小二乘法111
10．1最小二乘法拟合111
10．2实现112
10．3残差113
10．4估计114
10．5拟合优度116
10．6检验线性模型118
10．7加权重抽样119
10．8练习121
10．9术语121
第11章回归123
11．1StatsModels124
11．2多重回归125
11．3非线性关系127
11．4数据挖掘128
11．5预测129
11．6Logistic 回归131
11．7估计参数132
11．8实现133
11．9准确度134
11．10练习135
11．11术语136
第12章时间序列分析139
12．1导入和清洗数据139
12．2绘制图形141
12．3线性回归143
12．4移动平均值144
12．5缺失值146
12．6序列相关148
12．7自相关149
12．8预测150
12．9参考书目154
12．10练习154
12．11术语155
第13章生存分析157
13．1生存曲线157
13．2危险函数159
13．3估计生存曲线160
13．4Kaplan-Meier 估计161
13．5婚姻曲线162
13．6估计生存函数163
13．7置信区间164
13．8群组效应166
13．9外推168
13．10预期剩余生存期169
13．11练习171
13．12术语172
第14章分析方法173
14．1正态分布173
14．2抽样分布174
14．3表示正态分布175
14．4中心极限定理176
14．5检验CLT177
14．6应用CLT180
14．7相关检验181
14．8卡方检验183
14．9讨论184
14．10练习184
作者介绍186
封面介绍186

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