The Basic Practice of Statistics, 9th Edition
- Length: 800 pages
- Edition: 9
- Language: English
- Publisher: W. H. Freeman
- Publication Date: 2021-01-22
- ISBN-10: 1319383688
- ISBN-13: 9781319383688
- Sales Rank: #0 (See Top 100 Books)
Now available with Macmillan’s new online learning tool Achieve, the ninth edition of The Basic Practice of Statistics 9e teaches statistical thinking by guiding students through an investigative process of problem-solving with pedagogy designed to help students of all levels. Examples and exercises from a wide variety of topic areas use current, real data to provide students insight into how and why statistics are used to make decisions in the real world.
Achieve for The Basic Practice of Statistics connects the trusted Four-Step problem-solving approach and real world examples in the book to rich digital resources that foster further understanding and application of statistics. Assets in Achieve support learning before, during, and after class for students, while providing instructors with class performance analytics in an easy-to-use interface.
About this Book Cover Half Title Page Organizing a Statistical Problem: A Four-Step Process Title Page Copyright Page Brief Contents Contents Why Did You Do That? Preface Acknowledgments About the Authors Chapter 0 Getting Started 0.1 How the Data Were Obtained Matters 0.2 Always Look at the Data 0.3 Variation Is Everywhere 0.4 What Lies Ahead in This Book Chapter 0 Exercises Chapter 0 Exercises Part I Exploring Data Chapter 1 Picturing Distributions with Graphs 1.1 Individuals and Variables 1.2 Categorical Variables: Pie Charts and Bar Graphs 1.3 Quantitative Variables: Histograms 1.4 Interpreting Histograms 1.5 Quantitative Variables: Stemplots 1.6 Time Plots Chapter 1 Summary and Exercises Chapter 1 Summary Check Your Skills Chapter 1 Exercises Chapter 2 Describing Distributions with Numbers 2.1 Measuring Center: The Mean 2.2 Measuring Center: The Median 2.3 Comparing the Mean and the Median 2.4 Measuring Variability: The Quartiles 2.5 The Five-Number Summary and Boxplots 2.6 Spotting Suspected Outliers and Modified Boxplots 2.7 Measuring Variability: The Standard Deviation 2.8 Choosing Measures of Center and Variability 2.9 Examples of Technology 2.10 Organizing a Statistical Problem Chapter 2 Summary and Exercises Chapter 2 Summary Check Your Skills Chapter 2 Exercises Chapter 3 The Normal Distributions 3.1 Density Curves 3.2 Describing Density Curves 3.3 Normal Distributions 3.4 The 68–95–99.7 Rule 3.5 The Standard Normal Distribution 3.6 Finding Normal Proportions 3.7 Using the Standard Normal Table 3.8 Finding a Value Given a Proportion Chapter 3 Summary and Exercises Chapter 3 Summary Check Your Skills Chapter 3 Exercises Chapter 4 Scatterplots and Correlation 4.1 Explanatory and Response Variables 4.2 Displaying Relationships: Scatterplots 4.3 Interpreting Scatterplots 4.4 Adding Categorical Variables to Scatterplots 4.5 Measuring Linear Association: Correlation 4.6 Facts about Correlation Chapter 4 Summary and Exercises Chapter 4 Summary Check Your Skills Chapter 4 Exercises Chapter 5 Regression 5.1 Regression Lines 5.2 The Least-Squares Regression Line 5.3 Examples of Technology 5.4 Facts About Least-Squares Regression 5.5 Residuals 5.6 Influential Observations 5.7 Cautions About Correlation and Regression 5.8 Association Does Not Imply Causation 5.9 Correlation, Prediction, and Big Data Chapter 5 Summary and Exercises Chapter 5 Summary Check Your Skills Chapter 5 Exercises Chapter 6 Two-Way Tables 6.1 Marginal Distributions 6.2 Conditional Distributions 6.3 Simpson’s Paradox Chapter 6 Summary and Exercises Chapter 6 Summary Check Your Skills Chapter 6 Exercises Chapter 7 Exploring Data: Part I Review Part I Summary and Exercises Part I Skills Review Test Yourself Supplementary Exercises Part II Producing Data Chapter 8 Producing Data: Sampling 8.1 Population Versus Sample 8.2 How to Sample Badly 8.3 Simple Random Samples 8.4 Trustworthiness of Inference from Samples 8.5 Other Sampling Designs 8.6 Cautions About Sample Surveys 8.7 The Impact of Technology Chapter 8 Summary and Exercises Chapter 8 Summary Check Your Skills Chapter 8 Exercisse Chapter 9 Producing Data: Experiments 9.1 Observation Versus Experiment 9.2 Subjects, Factors, and Treatments 9.3 How to Experiment Badly 9.4 Randomized Comparative Experiments 9.5 The Logic of Randomized Comparative Experiments 9.6 Cautions About Experimentation 9.7 Matched Pairs and Other Block Designs Chapter 9 Summary and Exercises Chapter 9 Summary Check Your Skills Chapter 9 Exercises Chapter 10 Data Ethics* 10.1 Institutional Review Boards 10.2 Informed Consent 10.3 Confidentiality 10.4 Clinical Trials 10.5 Behavioral and Social Science Experiments Chapter 10 Summary and Exercises Chapter 10 Summary Chapter 10 Exercises Chapter 11 Producing Data: Part II Review Part II Summary and Exercises Part II Skills Review Test Yourself Supplementary Exercises Part III From Data Production to Inference Chapter 12 Introducing Probability 12.1 The Idea of Probability 12.2 The Search for Randomness* 12.3 Probability Models 12.4 Probability Rules 12.5 Finite Probability Models 12.6 Continuous Probability Models 12.7 Random Variables 12.8 Personal Probability* Chapter 12 Summary and Exercises Chapter 12 Summary Check Your Skills Chapter 12 Exercises Chapter 13 General Rules of Probability* 13.1 The General Addition Rule 13.2 Independence and the Multiplication Rule 13.3 Conditional Probability 13.4 The General Multiplication Rule 13.5 Showing That Events Are Independent 13.6 Tree Diagrams 13.7 Bayes’ Rule* Chapter 13 Summary and Exercises Chapter 13 Summary Check Your Skills Chapter 13 Exercises Chapter 14 Binomial Distributions* 14.1 The Binomial Setting and Binomial Distributions 14.2 Binomial Distributions in Statistical Sampling 14.3 Binomial Probabilities 14.4 Examples of Technology 14.5 Binomial Mean and Standard Deviation 14.6 The Normal Approximation to Binomial Distributions Chapter 14 Summary and Exercises Chapter 14 Summary Check Your Skills Chapter 14 Exercises Chapter 15 Sampling Distributions 15.1 Parameters and Statistics 15.2 Statistical Estimation and the Law of Large Numbers 15.3 Sampling Distributions 15.4 The Sampling Distribution of x 15.5 The Central Limit Theorem 15.6 Sampling Distributions and Statistical Significance Chapter 15 Summary and Exercises Chapter 15 Summary Check Your Skills Chapter 15 Exercises Chapter 16 Confidence Intervals: The Basics 16.1 The Reasoning of Statistical Estimation 16.2 Margin of Error and Confidence Level 16.3 Confidence Intervals for a Population Mean 16.4 How Confidence Intervals Behave Chapter 16 Summary and Exercises Chapter 16 Summary Check Your Skills Chapter 16 Exercises Chapter 17 Tests of Significance: The Basics 17.1 The Reasoning of Tests of Significance 17.2 Stating Hypotheses 17.3 P-Value and Statistical Significance 17.4 Tests for a Population Mean 17.5 Significance from a Table* Chapter 17 Summary and Exercises Chapter 17 Summary Check Your Skills Chapter 17 Exercises Chapter 18 Inference in Practice 18.1 Conditions for Inference in Practice 18.2 Cautions about Confidence Intervals 18.3 Cautions about Significance Tests 18.4 Planning Studies: Sample Size for Confidence Intervals 18.5 Planning Studies: The Power of a Statistical Test of Significance* Chapter 18 Summary and Exercises Chapter 18 Summary Check Your Skills Chapter 18 Exercises Chapter 19 From Data Production to Inference: Part III Review Part III Summary and Exercises Part III Skills Review Test Yourself Supplementary Exercises Part IV Inference about Variables Chapter 20 Inference about a Population Mean 20.1 Conditions for Inference about a Mean 20.2 The t Distributions 20.3 The One-Sample t Confidence Interval 20.4 The One-Sample t Test 20.5 Examples of Technology 20.6 Matched Pairs t Procedures 20.7 Robustness of t Procedures Chapter 20 Summary and Exercises Chapter 20 Summary Check Your Skills Chapter 20 Exercises Chapter 21 Comparing Two Means 21.1 Two-Sample Problems 21.2 Comparing Two Population Means 21.3 Two-Sample t Procedures 21.4 Examples of Technology 21.5 Robustness Again 21.6 Details of the t Approximation* 21.7 Avoid the Pooled Two-Sample t Procedures* 21.8 Avoid Inference about Standard Deviations* Chapter 21 Summary and Exercises Chapter 21 Summary Check Your Skills Chapter 21 Exercises Chapter 22 Inference about a Population Proportion 22.1 The Sample Proportion p^ 22.2 Large-Sample Confidence Intervals for a Proportion 22.3 Choosing the Sample Size 22.4 Significance Tests for a Proportion 22.5 Plus Four Confidence Intervals for a Proportion* Chapter 22 Summary and Exercises Chapter 22 Summary Check Your Skills Chapter 22 Exercises Chapter 23 Comparing Two Proportions 23.1 Two-Sample Problems: Proportions 23.2 The Sampling Distribution of a Difference between Proportions 23.3 Large-Sample Confidence Intervals for Comparing Proportions 23.4 Examples of Technology 23.5 Significance Tests for Comparing Proportions 23.6 Plus Four Confidence Intervals for Comparing Proportions* Chapter 23 Summary and Exercises Chapter 23 Summary Check Your Skills Chapter 23 Exercises Chapter 24 Inference about Variables: Part IV Review Part IV Summary and Exercises Skills Review Test Yourself Supplementary Exercises Part V Inference about Relationships Chapter 25 Two Categorical Variables: The Chi-Square Test 25.1 Two-Way Tables 25.2 The Problem of Multiple Comparisons 25.3 Expected Counts in Two-Way Tables 25.4 The Chi-Square Statistic 25.5 Examples of Technology 25.6 The Chi-Square Distributions 25.7 Cell Counts Required for the Chi-Square Test 25.8 Uses of the Chi-Square Test: Independence and Homogeneity 25.9 The Chi-Square Test for Goodness of Fit Chapter 25 Summary and Exercises Chapter 25 Summary Chapter 25 Skills Review Check Your Skills Chapter 25 Exercises Chapter 26 Inference for Regression 26.1 Conditions for Regression Inference 26.2 Estimating the Parameters 26.3 Examples of Technology 26.4 Testing the Hypothesis of No Linear Relationship 26.5 Testing Lack of Correlation 26.6 Confidence Intervals for the Regression Slope 26.7 Inference about Prediction 26.8 Checking the Conditions for Inference Chapter 26 Summary and Exercises Chapter 26 Summary Chapter 26 Skills Review Check Your Skills Chapter 26 Exercises Chapter 27 One-Way Analysis of Variance: Comparing Several Means 27.1 Comparing Several Means 27.2 The Analysis of Variance F Test 27.3 Using Technology 27.4 The Idea of Analysis of Variance 27.5 Conditions for ANOVA 27.6 F Distributions and Degrees of Freedom 27.7 Follow-Up Analysis: Tukey Pairwise Multiple Comparisons 27.8 Some Details of ANOVA Chapter 27 Summary and Exercises Chapter 27 Summary Chapter 27 Skills Review Check Your Skills Chapter 27 Exercises Part Vi Optional Companion Chapters Chapter 28 Nonparametric Tests 28.1 Comparing Two Samples: The Wilcoxon Rank Sum Test 28.2 The Normal Approximation for W 28.3 Examples of Technology 28.4 What Hypotheses Does Wilcoxon Test? 28.5 Dealing with Ties in Rank Tests 28.6 Matched Pairs: The Wilcoxon Signed Rank Test 28.7 The Normal Approximation for W 28.8 Dealing with Ties in the Signed Rank Test 28.9 Comparing Several Samples: The Kruskal–Wallis Test 28.10 Hypotheses and Conditions for the Kruskal–Wallis Test 28.11 The Kruskal–Wallis Test Statistic Chapter 28 Summary and Exercises Chapter 28 Summary Chapter 28 Skills Review Check Your Skills Chapter 28 Exercises Exploring The Web Notes and Data Sources Chapter 29 Multiple Regression* 29.1 Adding a Categorical Variable in Regression 29.2 Estimating Parameters 29.3 Examples of Technology 29.4 Inference for Multiple Regression 29.5 Interaction 29.6 A Model with Two Regression Lines 29.7 The General Multiple Linear Regression Model 29.8 Correlations between Explanatory Variables 29.9 A Case Study for Multiple Regression 29.10 Inference for Regression Parameters 29.11 Checking the Conditions for Inference Chapter 29 Summary and Exercises Chapter 29 Summary Chapter 29 Skills Review Check Your Skills Chapter 29 Exercises Exploring The Web Notes and Data Sources Chapter 30 Two-Way Analysis of Variance 30.1 Beyond One-Way ANOVA 30.2 Two-Way ANOVA: Conditions, Main Effects, and Interaction 30.3 Inference for Two-Way ANOVA 30.4 Some Details of Two-Way ANOVA* Chapter 30 Summary and Exercises Chapter 30 Summary Chapter 30 Skills Review Check Your Skills Chapter 30 Exercises Exploring The Web Notes and Data Sources Chapter 31 Statistical Process Control 31.1 Processes 31.2 Describing Processes 31.3 The Idea of Statistical Process Control 31.4 x Charts for Process Monitoring 31.5 s Charts for Process Monitoring 31.6 Using Control Charts 31.7 Setting Up Control Charts 31.8 Comments on Statistical Control 31.9 Don’t Confuse Control with Capability 31.10 Control Charts for Sample Proportions 31.11 Control Limits for p Charts Chapter 31 Summary and Exercises Chapter 31 Summary Chapter 31 Skills Review Check Your Skills Chapter 31 Exercises Exploring The Web Chapter 31 Notes and Data Sources Chapter 32 Resampling: Permutation Tests and the Bootstrap 32.1 Randomization in Experiments as a Basis for Inference 32.2 Permutation Tests for Two Treatments with Software 32.3 Generating Bootstrap Samples 32.4 Bootstrap Standard Errors and Confidence Intervals Chapter 32 Summary and Exercises Chapter 32 Summary Chapter 32 Skills Review Check Your Skills Chapter 32 Exercises Exploring The Web Notes and Data Sources Notes and Data Sources Tables Answers to Selected Exercises Chapter 0 – Getting Started Chapter 1 – Picturing Distributions with Graphs Chapter 2 – Describing Distributions with Numbers Chapter 3 – The Normal Distributions Chapter 4 – Scatterplots and Correlation Chapter 5 – Regression Chapter 6 – Two–Way Tables Chapter 7 – Exploring Data: Part I Review Chapter 8 – Producing Data: Sampling Chapter 9 – Producing Data: Experiments Chapter 10 – Data Ethics Chapter 11 – Producing Data: Part II Review Chapter 12 – Introducing Probability Chapter 13 – General Rules of Probability Chapter 14 – Binomial Distributions Chapter 15 – Sampling Distributions Chapter 16 – Confidence Intervals: The Basics Chapter 17 – Tests of Significance: The Basics Chapter 18 – Inference in Practice Chapter 19 – From Data Production to Inference: Part III Review Chapter 20 – Inference about a Population Mean Chapter 21 – Comparing Two Means Chapter 22 – Inference about a Population Proportion Chapter 23 – Comparing Two Proportions Chapter 24 – Inference about Variables: Part IV Review Chapter 25 – Two Categorical Variables: The Chi-Square Test Chapter 26 – Inference for Regression Chapter 27 – One–Way Analysis of Variance: Comparing Several Means Index Back Cover
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