Asia Pacific University Library catalogue


Practical statistics for data scientists : 50 essential concepts / Peter Bruce and Andrew Bruce.

By: Bruce, PeterContributor(s): Bruce, AndrewMaterial type: TextTextPublication details: Sebastopol, CA : O'Reilly Media, Inc., 2017Edition: 1st edDescription: xvi, 298 p. : ill. ; 24 cmISBN: 9781491952962 (pbk.); 1491952962 (pbk.)Other title: 50 essential concepts | Fifty essential conceptsSubject(s): Statistics -- Data processing | StatisticsLOC classification: QA276.4 | .B78 2017
Contents:
Copyright; Table of Contents; Preface; What to Expect; Conventions Used in This Book; Using Code Examples; Safari® Books Online; How to Contact Us; Acknowledgments; Chapter 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 PopulationFurther 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; Chapter 2. Data and Sampling Distributions.
Random Sampling and Sample BiasBias; 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 DistributionsPoisson Distributions; Exponential Distribution; Estimating the Failure Rate; Weibull Distribution; Further Reading; Summary; Chapter 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-ValuesP-Value; Alpha; Type 1 and Type 2 Errors; Data Science 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; Chapter 4. Regression and Prediction.
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Includes bibliographical references and index.

Copyright; Table of Contents; Preface; What to Expect; Conventions Used in This Book; Using Code Examples; Safari® Books Online; How to Contact Us; Acknowledgments; Chapter 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 PopulationFurther 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; Chapter 2. Data and Sampling Distributions.

Random Sampling and Sample BiasBias; 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 DistributionsPoisson Distributions; Exponential Distribution; Estimating the Failure Rate; Weibull Distribution; Further Reading; Summary; Chapter 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-ValuesP-Value; Alpha; Type 1 and Type 2 Errors; Data Science 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; Chapter 4. Regression and Prediction.

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