Description

Book Synopsis

Statistics: Unlocking the Power of Data, 2ndEditioncontinues to utilize these intuitive methods like randomization and bootstrap intervals to introduce the fundamental idea of statistical inference.These methods are brought to life through authentically relevant examples and are accessible at very early stages of the text.


Applications are drawn from a wide variety of disciplines, chosen primarily on the basis of perceived interest to students and instructors. Problems and exercises are plentiful and span a wide range of difficulty levels, from very straightforward short answer problems to extended projects.



Table of Contents

Preface ix

Unit A: Data 1

Chapter 1. Collecting Data 2

1.1. The Structure of Data 4

1.2. Sampling from a Population 16

1.3. Experiments and Observational Studies 29

Chapter 2. Describing Data 46

2.1. Categorical Variables 48

2.2. One Quantitative Variable: Shape and Center 63

2.3. One Quantitative Variable: Measures of Spread 77

2.4. Boxplots and Quantitative/Categorical Relationships 93

2.5. Two Quantitative Variables: Scatterplot and Correlation 106

2.6. Two Quantitative Variables: Linear Regression 123

2.7. Data Visualization and Multiple Variables 137

Unit A: Essential Synthesis 161

Review Exercises 174

Projects Online

Unit B: Understanding Inference 193

Chapter 3. Confidence Intervals 194

3.1. Sampling Distributions 196

3.2. Understanding and Interpreting Confidence Intervals 213

3.3. Constructing Bootstrap Confidence Intervals 228

3.4. Bootstrap Confidence Intervals using Percentiles 242

Chapter 4. Hypothesis Tests 256

4.1. Introducing Hypothesis Tests 258

4.2. Measuring Evidence with P-values 272

4.3. Determining Statistical Significance 288

4.4. A Closer Look at Testing 303

4.5. Making Connections 318

Unit B: Essential Synthesis 341

Review Exercises 351

Projects Online

Unit C: Inference with Normal and t-Distributions 369

Chapter 5. Approximating with a Distribution 370

5.1. Hypothesis Tests Using Normal Distributions 372

5.2. Confidence Intervals Using Normal Distributions 387

Chapter 6. Inference for Means and Proportions 402

6.1. Inference for a Proportion

6.1-D Distribution of a Proportion 404

6.1-CI Confidence Interval for a Proportion 407

6.1-HT Hypothesis Test for a Proportion 414

6.2. Inference for a Mean

6.2-D Distribution of a Mean 419

6.2-CI Confidence Interval for a Mean 424

6.2-HT Hypothesis Test for a Mean 433

6.3. Inference for a Difference in Proportions

6.3-D Distribution of a Difference in Proportions 438

6.3-CI Confidence Interval for a Difference in Proportions 441

6.3-HT Hypothesis Test for a Difference in Proportions 446

6.4. Inference for a Difference in Means

6.4-D Distribution of a Difference in Means 452

6.4-CI Confidence Interval for a Difference in Means 455

6.4-HT Hypothesis Test for a Difference in Means 461

6.5. Paired Difference in Means 468

Unit C: Essential Synthesis 477

Review Exercises 489

Projects Online

Unit D: Inference for Multiple Parameters 505

Chapter 7. Chi-Square Tests for Categorical Variables 506

7.1. Testing Goodness-of-Fit for a Single Categorical Variable 508

7.2. Testing for an Association between Two Categorical Variables 523

Chapter 8. ANOVA to Compare Means 538

8.1. Analysis of Variance 540

8.2. Pairwise Comparisons and Inference after ANOVA 563

Chapter 9. Inference for Regression 574

9.1. Inference for Slope and Correlation 576

9.2. ANOVA for Regression 591

9.3. Confidence and Prediction Intervals 603

Chapter 10. Multiple Regression 610

10.1. Multiple Predictors 612

10.2. Checking Conditions for a Regression Model 624

10.3. Using Multiple Regression 633

Unit D: Essential Synthesis 647

Review Exercises 661

Projects Online

The Big Picture: Essential Synthesis 669

Exercises for the Big Picture: Essential Synthesis 683

Chapter P. Probability Basics 688

P.1. Probability Rules 690

P.2. Tree Diagrams and Bayes’ Rule 702

P.3. Random Variables and Probability Functions 709

P.4. Binomial Probabilities 716

P.5. Density Curves and the Normal Distribution 724

Appendix A. Chapter Summaries 737

Appendix B. Selected Dataset Descriptions 749

Partial Answers 761

Index

General Index 783

Data Index 786

Statistics

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    A Paperback / softback by Robin H. Lock, Patti Frazer Lock, Kari Lock Morgan

    10 in stock

      Trusted by thousands of customers. See 2,385+ Customer Reviews

      View other formats and editions of Statistics by Robin H. Lock

      Publisher: John Wiley & Sons Inc
      Publication Date: Publication Date: 27/01/2020
      ISBN13: 9781119657187, 978-1119657187
      ISBN10: 1119657180

      Description

      Book Synopsis

      Statistics: Unlocking the Power of Data, 2ndEditioncontinues to utilize these intuitive methods like randomization and bootstrap intervals to introduce the fundamental idea of statistical inference.These methods are brought to life through authentically relevant examples and are accessible at very early stages of the text.


      Applications are drawn from a wide variety of disciplines, chosen primarily on the basis of perceived interest to students and instructors. Problems and exercises are plentiful and span a wide range of difficulty levels, from very straightforward short answer problems to extended projects.



      Table of Contents

      Preface ix

      Unit A: Data 1

      Chapter 1. Collecting Data 2

      1.1. The Structure of Data 4

      1.2. Sampling from a Population 16

      1.3. Experiments and Observational Studies 29

      Chapter 2. Describing Data 46

      2.1. Categorical Variables 48

      2.2. One Quantitative Variable: Shape and Center 63

      2.3. One Quantitative Variable: Measures of Spread 77

      2.4. Boxplots and Quantitative/Categorical Relationships 93

      2.5. Two Quantitative Variables: Scatterplot and Correlation 106

      2.6. Two Quantitative Variables: Linear Regression 123

      2.7. Data Visualization and Multiple Variables 137

      Unit A: Essential Synthesis 161

      Review Exercises 174

      Projects Online

      Unit B: Understanding Inference 193

      Chapter 3. Confidence Intervals 194

      3.1. Sampling Distributions 196

      3.2. Understanding and Interpreting Confidence Intervals 213

      3.3. Constructing Bootstrap Confidence Intervals 228

      3.4. Bootstrap Confidence Intervals using Percentiles 242

      Chapter 4. Hypothesis Tests 256

      4.1. Introducing Hypothesis Tests 258

      4.2. Measuring Evidence with P-values 272

      4.3. Determining Statistical Significance 288

      4.4. A Closer Look at Testing 303

      4.5. Making Connections 318

      Unit B: Essential Synthesis 341

      Review Exercises 351

      Projects Online

      Unit C: Inference with Normal and t-Distributions 369

      Chapter 5. Approximating with a Distribution 370

      5.1. Hypothesis Tests Using Normal Distributions 372

      5.2. Confidence Intervals Using Normal Distributions 387

      Chapter 6. Inference for Means and Proportions 402

      6.1. Inference for a Proportion

      6.1-D Distribution of a Proportion 404

      6.1-CI Confidence Interval for a Proportion 407

      6.1-HT Hypothesis Test for a Proportion 414

      6.2. Inference for a Mean

      6.2-D Distribution of a Mean 419

      6.2-CI Confidence Interval for a Mean 424

      6.2-HT Hypothesis Test for a Mean 433

      6.3. Inference for a Difference in Proportions

      6.3-D Distribution of a Difference in Proportions 438

      6.3-CI Confidence Interval for a Difference in Proportions 441

      6.3-HT Hypothesis Test for a Difference in Proportions 446

      6.4. Inference for a Difference in Means

      6.4-D Distribution of a Difference in Means 452

      6.4-CI Confidence Interval for a Difference in Means 455

      6.4-HT Hypothesis Test for a Difference in Means 461

      6.5. Paired Difference in Means 468

      Unit C: Essential Synthesis 477

      Review Exercises 489

      Projects Online

      Unit D: Inference for Multiple Parameters 505

      Chapter 7. Chi-Square Tests for Categorical Variables 506

      7.1. Testing Goodness-of-Fit for a Single Categorical Variable 508

      7.2. Testing for an Association between Two Categorical Variables 523

      Chapter 8. ANOVA to Compare Means 538

      8.1. Analysis of Variance 540

      8.2. Pairwise Comparisons and Inference after ANOVA 563

      Chapter 9. Inference for Regression 574

      9.1. Inference for Slope and Correlation 576

      9.2. ANOVA for Regression 591

      9.3. Confidence and Prediction Intervals 603

      Chapter 10. Multiple Regression 610

      10.1. Multiple Predictors 612

      10.2. Checking Conditions for a Regression Model 624

      10.3. Using Multiple Regression 633

      Unit D: Essential Synthesis 647

      Review Exercises 661

      Projects Online

      The Big Picture: Essential Synthesis 669

      Exercises for the Big Picture: Essential Synthesis 683

      Chapter P. Probability Basics 688

      P.1. Probability Rules 690

      P.2. Tree Diagrams and Bayes’ Rule 702

      P.3. Random Variables and Probability Functions 709

      P.4. Binomial Probabilities 716

      P.5. Density Curves and the Normal Distribution 724

      Appendix A. Chapter Summaries 737

      Appendix B. Selected Dataset Descriptions 749

      Partial Answers 761

      Index

      General Index 783

      Data Index 786

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