面向数据科学家的实用统计学(第2版影印版)(英文版)

统计方法是数据科学 的关键部分，但鲜有数据 科学家接受过正规的统计 培训。基础统计学的相关 课程和书籍很少从数据科 学的角度来介绍这个主题 。这本广受欢迎的指南手 册的第二版添加了Python 综合示例，提供了将统计 方法应用于数据科学的实 用指导，告诉你如何避免 误用这些方法，并就什么 重要，什么不重要给出了 建议。许多数据科学资源 都引入了统计方法，但是 缺乏更深层次的统计视角 。如果你熟悉R或Python 编程语言，对统计学有所 了解，那么这本快速参考 将以其通俗易懂的格式弥 补这种空白。

Preface 1. Exploratory Data Analysis Elements of Structured Data Further Reading Rectangular Data Data Frames and Indexes Nonrectangular Data Structures Further Reading Estimates of Location Mean Median and Robust Estimates Example: Location Estimates of Population and Murder Rates Further Reading Estimates of Variability Standard Deviation and Related Estimates Estimates Based on Percentiles Example: Variability Estimates of State Population Further Reading Exploring the Data Distribution Percentiles and Boxplots Frequency Tables and Histograms Density Plots and Estimates Further Reading Exploring Binary and Categorical Data Mode Expected Value Probability Further Reading Correlation Scatterplots Further Reading Exploring Two or More Variables Hexagonal Binning and Contours (Plotting Numeric Versus Numeric Data) Two Categorical Variables Categorical and Numeric Data Visualizing Multiple Variables Further Reading Summary 2. Data and Sampling Distributions Random Sampling and Sample Bias Bias Random Selection Size Versus Quality: When Does Size Matter? Sample Mean Versus Population Mean Further Reading Selection Bias Regression to the Mean Further Reading Sampling Distribution of a Statistic Central Limit Theorem Standard Error Further Reading The Bootstrap Resampling Versus Bootstrapping Further Reading Confidence Intervals Further Reading Normal Distribution Standard Normal and QQ-Plots Long-Tailed Distributions Further Reading Student's t-Distribution Further Reading Binomial Distribution Further Reading Chi-Square Distribution Further Reading F-Distribution …… 3. Statistical Experiments and Significance Testing 4. Regression and Prediction 5. Classification 6. Statistical Machine Learning 7. Unsupervised Learning Bibliography Index