Introduction to Statistical Investigations, Second Edition provides a unified framework for explaining variation across study designs and variable types, helping students increase their statistical literacy and appreciate the indispensable role of statistics in scientific research. Requiring only basic algebra as a prerequisite, the program uses the immersive, simulation-based inference approach for which the author team is known. Students engage with various aspects of data collection and analysis using real data and clear explanations designed to strengthen multivariable understanding and reinforce concepts.
Each chapter follows a coherent six-step statistical exploration and investigation method (ask a research question, design a study, explore the data, draw inferences, formulate conclusions, and look back and ahead) enabling students to assess a variety of concepts in a single assignment. Challenging questions based on research articles strengthen critical reading skills, fully worked examples demonstrate essential concepts and methods, and engaging visualizations illustrate key themes of explained variation. The end-of-chapter investigations expose students to various applications of statistics in the real world using real data from popular culture and published research studies in variety of disciplines. Accompanying examples throughout the text, user-friendly applets enable students to conduct the simulations and analyses covered in the book.
PRELIMINARIES
Introduction to Statistical
Investigations 1
SECTION P.1 Introduction to the Six-Step Method 2
SECTION P.2 Exploring Data 6
SECTION P.3 Exploring Random Processes 10
UNIT 1 FOUR PILLARS OF INFERENCE: STRENGTH, SIZE, BREADTH, AND CAUSE 21
CHAPTER 1 Significance: How Strong Is the Evidence? 22
SECTION 1.1 Introduction to Chance Models 23
SECTION 1.2 Measuring the Strength of Evidence 35
SECTION 1.3 Alternative Measure of Strength of Evidence 46
SECTION 1.4 What Impacts Strength of Evidence? 53
SECTION 1.5 Inference for a Single Proportion: Theory-Based Approach 63
CHAPTER 2 Generalization: How Broadly Do the Results Apply? 102
SECTION 2.1 Sampling from a Finite Population 103
SECTION 2.2 Inference for a Single Quantitative Variable 120
SECTION 2.3 Errors and Significance 138
CHAPTER 3 Estimation: How Large Is the Effect? 163
SECTION 3.1 Statistical Inference: Confidence Intervals 164
SECTION 3.2 2SD and Theory-Based Confidence Intervals for a Single Proportion 173
SECTION 3.3 2SD and Theory-Based Confidence Intervals for a Single Mean 181
SECTION 3.4 Factors that Affect the Width of a Confidence Interval 187
SECTION 3.5: Cautions When Conducting Inference 194
CHAPTER 4 Causation: Can We Say What Caused the Effect? 231
SECTION 4.1 Association and Confounding 232
SECTION 4.2 Observational Studies versus Experiments 237
UNIT 2 COMPARING TWO GROUPS 259 CHAPTER 5
Comparing Two Proportions 260
SECTION 5.1 Comparing Two Groups: Categorical Response 261
SECTION 5.2 Comparing Two Proportions: Simulation-Based Approach 267
SECTION 5.3 Comparing Two Proportions: Theory-Based Approach 283
CHAPTER 6 Comparing Two Means 323
SECTION 6.1 Comparing Two Groups: Quantitative Response 324
SECTION 6.2 Comparing Two Means: Simulation-Based Approach 331
SECTION 6.3 Comparing Two Means: Theory-Based Approach 346
CHAPTER 7 Paired Data: One Quantitative Variable 382
SECTION 7.1 Paired Designs 383
SECTION 7.2 Analyzing Paired Data: Simulation-Based Approach 388
SECTION 7.3 Analyzing Paired Data: Theory-Based Approach 399
UNIT 3 ANALYZING MORE GENERAL SITUATIONS 427
CHAPTER 8 Comparing More Than Two Proportions 429
SECTION 8.1 Comparing Multiple Proportions: Simulation-Based Approach 430
SECTION 8.2 Comparing Multiple Proportions: Theory-Based Approach 440
CHAPTER 9 Comparing More Than Two Means 475
SECTION 9.1 Comparing Multiple Means: Simulation-Based Approach 476
SECTION 9.2 Comparing Multiple Means: Theory-Based Approach 485
CHAPTER 10 Two Quantitative Variables 520
SECTION 10.1 Two Quantitative Variables: Scatterplots and Correlation 521
SECTION 10.2 Inference for the Correlation Coefficient: Simulation-Based Approach 529
SECTION 10.3 Least Squares Regression 538
SECTION 10.4 Inference for the Regression Slope: Simulation-Based Approach 547
SECTION 10.5 Inference for the Regression Slope: Theory-Based Approach 552
APPENDIX A Calculation Details 592
APPENDIX B Stratified and Cluster Samples 610
SOLUTIONS TO SELECTED EXERCISES 615
INDEX