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Essential Statistics, Global Edition

Essential Statistics, Global Edition

Robert N. Gould | Colleen N. Ryan | Rebecca Wong

(2016)

Additional Information

Book Details

Abstract

This book is ideal for a one-semester course in statistics, offering a streamlined presentation of Introductory Statistics: Exploring the World through Data, by Gould/Ryan.

 

Exploring the World through Data

We live in a data-driven world, and the goal of this text is to teach students how to access and analyze these data critically. Authors Rob Gould, Colleen Ryan, and Rebecca Wong want students to develop a "data habit of mind" because learning statistics is an essential life skill that extends beyond the classroom. Regardless of their math backgrounds, students will learn how to think about data and how to reason using data. With a clear, unintimidating writing style and carefully chosen pedagogy, this text makes data analysis accessible to all students.

 

MyStatLab not included. Students, if MyStatLab is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN and course ID. MyStatLab should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information.


MyStatLab from Pearson is the world’s leading online resource for teaching and learning statistics, integrating interactive homework, assessment, and media in a flexible, easy-to-use format. MyStatLab is a course management system that delivers improving results in helping individual students succeed.

Table of Contents

Section Title Page Action Price
Cover Cover
Title Page 3
Copyright Page 4
Dedication 5
About the Authors 6
Contents 7
Preface 11
Acknowledgments 15
Index of Applications 21
Chapter 1: Introduction to Data 26
Case Study: Deadly Cell Phones? 27
1.1. What Are Data? 28
1.2. Classifying and Storing Data 30
1.3. Organizing Categorical Data 34
1.4. Collecting Data to Understand Causality 39
Exploring Statistics: Collecting a Table of Different Kinds of Data 49
Chapter 2: Picturing Variation with Graphs 60
Case Study: Student-to-Teacher Ratio at Colleges 61
2.1. Visualizing Variation in Numerical Data 62
2.2. Summarizing Important Features of a Numerical Distribution 67
2.3. Visualizing Variation in Categorical Variables 75
2.4. Summarizing Categorical Distributions 78
2.5. Interpreting Graphs 81
Exploring Statistics: Personal Distance 85
Chapter 3: Numerical Summaries of Center and Variation 106
Case Study: Living in a Risky World 107
3.1. Summaries for Symmetric Distributions 108
3.2. What’s Unusual? The Empirical Rule and z-Scores 118
3.3. Summaries for Skewed Distributions 123
3.4. Comparing Measures of Center 130
3.5. Using Boxplots for Displaying Summaries 135
Exploring Statistics: Does Reaction Distance Depend on Gender? 142
Chapter 4: Regression Analysis: Exploring Associations between Variables 166
Case Study: Catching Meter Thieves 167
4.1. Visualizing Variability with a Scatterplot 168
4.2. Measuring Strength of Association with Correlation 172
4.3. Modeling Linear Trends 180
4.4. Evaluating the Linear Model 193
Exploring Statistics: Guessing the Age of Famous People 201
Chapter 5: Modeling Variation with Probability 228
Case Study: SIDS or Murder? 229
5.1. What Is Randomness? 230
5.2. Finding Theoretical Probabilities 233
5.3. Associations in Categorical Variables 242
5.4. Finding Empirical Probabilities 252
Exploring Statistics: Let’s Make a Deal: Stay or Switch? 257
Chapter 6: Modeling Random Events: The Normal and Binomial Models 272
Case Study: You Sometimes Get More Than You Pay For 273
6.1. Probability Distributions Are Models of Random Experiments 274
6.2. The Normal Model 279
6.3. The Binomial Model (optional) 292
Exploring Statistics: ESP with Coin Flipping 307
Chapter 7: Survey Sampling and Inference 324
Case Study: Spring Break Fever: Just What the Doctors Ordered? 325
7.1. Learning about the World through Surveys 326
7.2. Measuring the Quality of a Survey 332
7.3. The Central Limit Theorem for Sample Proportions 340
7.4. Estimating the Population Proportion with Confidence Intervals 347
7.5. Comparing Two Population Proportions with Confidence 354
Exploring Statistics: Simple Random Sampling Prevents Bias 361
Chapter 8: Hypothesis Testing for Population Proportions 378
Case Study: Dodging the Question 379
8.1. The Essential Ingredients of Hypothesis Testing 380
8.2. Hypothesis Testing in Four Steps 387
8.3. Hypothesis Tests in Detail 396
8.4. Comparing Proportions from Two Populations 403
Exploring Statistics: Identifying Flavors of Gum through Smell 411
Chapter 9: Inferring Population Means 428
Case Study: Epilepsy Drugs and Children 429
9.1. Sample Means of Random Samples 430
9.2. The Central Limit Theorem for Sample Means 434
9.3. Answering Questions about the Mean of a Population 441
9.4. Hypothesis Testing for Means 451
9.5. Comparing Two Population Means 457
9.6. Overview of Analyzing Means 472
Exploring Statistics: Pulse Rates 476
Chapter 10: Analyzing Categorical Variables and Interpreting Research 500
Case Study: Popping Better Popcorn 501
10.1. The Basic Ingredients for Testing with Categorical Variables 502
10.2. Chi-Square Tests for Associations between Categorical Variables 509
10.3. Reading Research Papers 518
Exploring Statistics: Skittles 527
Appendix A: Tables 543
Appendix B: Check Your Tech Answers 551
Appendix C: Answers to Odd-Numbered Exercises 553
Appendix D: Credits 575
Index 577
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