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 QQ-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 …… 3. Statistical Experiments and Significance Testing 4. Regression and Prediction 5. Classification 6. Statistical Machine Learning 7. Unsupervised Learning Bibliography Index
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