面向数据科学家的实用统计学(影印版)(英文版) pdf epub mobi txt 电子书 下载 2025

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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 Table and Histograms
Density Estimates
Further Reading
Exploring Binary and Categorical Data
Mode
Expected Value
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 Q Q—Plots
Long—Tailed Distributions
Further Reading
Student's t—Distribution
Further Reading
Binomial Distribution
Further Reading
Poisson and Related Distributions
Poisson Distributions
Exponential Distribution
Estimating the Failure Rate
Weibull Distribution
Further Reading
Summary
3.Statistical Experiments and Significance Testing
A／B Testing
Why Have a Control Group？
Why Just A／B？ Why Not C， D...？
For Further Reading
Hypothesis Tests
The Null Hypothesis
Alternative Hypothesis
One—Way， Two—Way Hypothesis Test
Further Reading
Resampling
Permutation Test
Example：Web Stickiness
Exhaustive and Bootstrap Permutation Test
Permutation Tests： The Bottom Line for Data Science
For Further Reading
Statistical Significance and P—Values
P—Value
Alpha
Type 1 and Type 2 Errors
Data Saence and P—Values
Further Reading
t—Tests
Further Reading
Multiple Testing
Further Reading
Degrees of Freedom
Further Reading
ANOVA
F—Statistic
Two—Way ANOVA
Further Reading
Chi—Square Test
Chi—Square Test： A Resampling Approach
Chi—Squared Test： Statistical Theory
Fisher's Exact Test
Relevance for Data Science
Further Reading
Multi—Arm Bandit Algorithm
Further Reading
Power and Sample Size
Sample Size
Further Reading
Summary
……
4.Regression and Prediction
5.Classification
6.Statistical Machine Learning
7.Unsupervised Learning
Bibliography
Index
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