Statistical Methods, Fourth Edition, is designed to introduce students to a wide-range of popular and practical statistical techniques. Requiring a minimum of advanced mathematics, it is suitable for undergraduates in statistics, or graduate students in the physical, life, and social sciences. By providing an overview of statistical reasoning, this text equips readers with the insight needed to summarize data, recognize good experimental designs, implement appropriate analyses, and arrive at sound interpretations of statistical results.
1. 1.1: Introduction - p. 1 2. 1.2: Observations and Variables - p. 5 3. 1.3: Types of Measurements for Variables - p. 7 4. 1.4: Distributions - p. 13 5. 1.5: Numerical Descriptive Statistics - p. 19 6. 1.6: Exploratory Data Analysis - p. 33 7. 1.7: Bivariate Data - p. 37 8. 1.8: Populations, Samples, and Statistical Inference — A Preview - p. 42 9. 1.9: Data Collection - p. 43 10. 1.10: Chapter Summary - p. 45 11. Summary - p. 48 12. 1.11: Chapter Exercises - p. 49 13. Chapter 2 Probability and Sampling Distributions - p. 65 14. 2.1: Introduction - p. 66 15. 2.2: Probability - p. 69 16. 2.3: Discrete Probability Distributions - p. 78 17. 2.4: Continuous Probability Distributions - p. 85 18. 2.5: Sampling Distributions - p. 96 19. 2.6: Other Sampling Distributions - p. 106 20. 2.7: Chapter Summary - p. 114 21. 2.8: Chapter Exercises - p. 114 22. Chapter 3 Principles of Inference - p. 123 23. 3.1: Introduction - p. 124 24. 3.2: Hypothesis Testing - p. 125 25. 3.3: Estimation - p. 147 26. 3.4: Sample Size - p. 152 27. 3.5: Assumptions - p. 155 28. 3.6: Chapter Summary - p. 157 29. 3.7: Chapter Exercises - p. 159 30. Exercises - p. 163 31. Chapter 4 Inferences on a Single Population - p. 169 32. Chapter 5 Inferences for Two Populations - p. 201 33. Chapter 6 Inferences for Two or More Means - p. 243 34. 6.1: Introduction - p. 244 35. 6.2: The Analysis of Variance - p. 245 36. 6.3: The Linear Model - p. 256 37. 6.4: Assumptions - p. 260 38. 6.5: Specific Comparisons - p. 265 39. 6.6: Random Models - p. 278 40. 6.7: Analysis of Means - p. 281 41. 6.8: Chapter Summary - p. 287 42. 6.9: Chapter Exercises - p. 288 43. Projects - p. 299 44. Chapter 7 Linear Regression - p. 301 45. 7.1: Introduction - p. 302 46. 7.2: The Regression Model - p. 304 47. 7.3: Estimation of Parameters β0 and β1 - p. 308 48. 7.4: Estimation of σ2 and the Partitioning of Sums of Squares - p. 312 49. 7.5: Inferences for Regression - p. 315 50. 7.6: Using Statistical Software - p. 325 51. 7.7: Correlation - p. 328 52. 7.8: Regression Diagnostics - p. 331 53. 7.9: Chapter Summary - p. 337 54. 7.10: Chapter Exercises - p. 340 55. Chapter 8 Multiple Regression - p. 351 56. 8.1: The Multiple Regression Model - p. 354 57. 8.2: Estimation of Coefficients - p. 357 58. 8.3: Inferential Procedures - p. 370 59. 8.4: Correlations - p. 384 60. 8.5: Using Statistical Software - p. 387 61. 8.6: Special Models - p. 390 62. 8.7: Multicollinearity - p. 399 63. 8.8: Variable Selection - p. 405 64. 8.9: Detection of Outliers, Row Diagnostics - p. 411 65. 8.10: Chapter Summary - p. 419 66. 8.11: Chapter Exercises - p. 423 67. Chapter 9 Factorial Experiments - p. 445 68. 9.1: Introduction - p. 446 69. 9.2: Concepts and Definitions - p. 447 70. 9.3: The Two-Factor Factorial Experiment - p. 450 71. 9.4: Specific Comparisons - p. 460 72. 9.5: Quantitative Factors - p. 468 73. 9.6: No Replications - p. 472 74. 9.7: Three or More Factors - p. 472 75. 9.8: Chapter Summary - p. 475 76. 9.9: Chapter Exercises - p. 479 77. Chapter 10 Design of Experiments - p. 493 78. 10.1: Introduction - p. 495 79. 10.2: The Randomized Block Design - p. 496 80. 10.3: Randomized Blocks with Sampling - p. 502 81. 10.4: Other Designs - p. 508 82. 10.5: Repeated Measures Designs - p. 515 83. 10.6: Chapter Summary - p. 529 84. 10.7: Chapter Exercises - p. 533 85. Chapter 11 Other Linear Models - p. 547 86. 11.1: Introduction - p. 547 87. 11.2: The Dummy Variable Model - p. 549 88. 11.3: Unbalanced Data - p. 554 89. 11.4: Statistical Software’s Implementation of the Dummy Variable Model - p. 556 90. 11.5: Models with Dummy and Interval Variables - p. 558 91. 11.6: Extensions to Other Models - p. 570 92. 11.7: Estimating Linear Combinations of Regression Parameters - p. 570 93. 11.8: Weighted Least Squares - p. 574 94. 11.9: Correlated Errors - p. 577 95. 11.10: Chapter Summary - p. 581 96. 11.11: Chapter Exercises - p. 583 97. Chapter 12 Categorical Data - p. 597 98. Chapter 13 Special Types of Regression - p. 623 99. Chapter 14 Nonparametric Methods - p. 651 100. Appendix A Tables of Distributions - p. 685 101. Appendix B - p. 699 102. Appendix B A Brief Introduction to Matrices - p. 700.e1 103. Appendix C Descriptions of Data Sets - p. 701 104. Hints for Selected Exercises - p. 707 105. References - p. 741 106. Index - p. 747
Statistical Methods, Fourth Edition, is designed to introduce students to a wide-range of popular and practical statistical techniques. Requiring a minimum of advanced mathematics, it is suitable for undergraduates in statistics, or graduate students in the physical, life, and social sciences. By providing an overview of statistical reasoning, this text equips readers with the insight needed to summarize data, recognize good experimental designs, implement appropriate analyses, and arrive at sound interpretations of statistical results.
1. 1.1: Introduction - p. 1 2. 1.2: Observations and Variables - p. 5 3. 1.3: Types of Measurements for Variables - p. 7 4. 1.4: Distributions - p. 13 5. 1.5: Numerical Descriptive Statistics - p. 19 6. 1.6: Exploratory Data Analysis - p. 33 7. 1.7: Bivariate Data - p. 37 8. 1.8: Populations, Samples, and Statistical Inference — A Preview - p. 42 9. 1.9: Data Collection - p. 43 10. 1.10: Chapter Summary - p. 45 11. Summary - p. 48 12. 1.11: Chapter Exercises - p. 49 13. Chapter 2 Probability and Sampling Distributions - p. 65 14. 2.1: Introduction - p. 66 15. 2.2: Probability - p. 69 16. 2.3: Discrete Probability Distributions - p. 78 17. 2.4: Continuous Probability Distributions - p. 85 18. 2.5: Sampling Distributions - p. 96 19. 2.6: Other Sampling Distributions - p. 106 20. 2.7: Chapter Summary - p. 114 21. 2.8: Chapter Exercises - p. 114 22. Chapter 3 Principles of Inference - p. 123 23. 3.1: Introduction - p. 124 24. 3.2: Hypothesis Testing - p. 125 25. 3.3: Estimation - p. 147 26. 3.4: Sample Size - p. 152 27. 3.5: Assumptions - p. 155 28. 3.6: Chapter Summary - p. 157 29. 3.7: Chapter Exercises - p. 159 30. Exercises - p. 163 31. Chapter 4 Inferences on a Single Population - p. 169 32. Chapter 5 Inferences for Two Populations - p. 201 33. Chapter 6 Inferences for Two or More Means - p. 243 34. 6.1: Introduction - p. 244 35. 6.2: The Analysis of Variance - p. 245 36. 6.3: The Linear Model - p. 256 37. 6.4: Assumptions - p. 260 38. 6.5: Specific Comparisons - p. 265 39. 6.6: Random Models - p. 278 40. 6.7: Analysis of Means - p. 281 41. 6.8: Chapter Summary - p. 287 42. 6.9: Chapter Exercises - p. 288 43. Projects - p. 299 44. Chapter 7 Linear Regression - p. 301 45. 7.1: Introduction - p. 302 46. 7.2: The Regression Model - p. 304 47. 7.3: Estimation of Parameters β0 and β1 - p. 308 48. 7.4: Estimation of σ2 and the Partitioning of Sums of Squares - p. 312 49. 7.5: Inferences for Regression - p. 315 50. 7.6: Using Statistical Software - p. 325 51. 7.7: Correlation - p. 328 52. 7.8: Regression Diagnostics - p. 331 53. 7.9: Chapter Summary - p. 337 54. 7.10: Chapter Exercises - p. 340 55. Chapter 8 Multiple Regression - p. 351 56. 8.1: The Multiple Regression Model - p. 354 57. 8.2: Estimation of Coefficients - p. 357 58. 8.3: Inferential Procedures - p. 370 59. 8.4: Correlations - p. 384 60. 8.5: Using Statistical Software - p. 387 61. 8.6: Special Models - p. 390 62. 8.7: Multicollinearity - p. 399 63. 8.8: Variable Selection - p. 405 64. 8.9: Detection of Outliers, Row Diagnostics - p. 411 65. 8.10: Chapter Summary - p. 419 66. 8.11: Chapter Exercises - p. 423 67. Chapter 9 Factorial Experiments - p. 445 68. 9.1: Introduction - p. 446 69. 9.2: Concepts and Definitions - p. 447 70. 9.3: The Two-Factor Factorial Experiment - p. 450 71. 9.4: Specific Comparisons - p. 460 72. 9.5: Quantitative Factors - p. 468 73. 9.6: No Replications - p. 472 74. 9.7: Three or More Factors - p. 472 75. 9.8: Chapter Summary - p. 475 76. 9.9: Chapter Exercises - p. 479 77. Chapter 10 Design of Experiments - p. 493 78. 10.1: Introduction - p. 495 79. 10.2: The Randomized Block Design - p. 496 80. 10.3: Randomized Blocks with Sampling - p. 502 81. 10.4: Other Designs - p. 508 82. 10.5: Repeated Measures Designs - p. 515 83. 10.6: Chapter Summary - p. 529 84. 10.7: Chapter Exercises - p. 533 85. Chapter 11 Other Linear Models - p. 547 86. 11.1: Introduction - p. 547 87. 11.2: The Dummy Variable Model - p. 549 88. 11.3: Unbalanced Data - p. 554 89. 11.4: Statistical Software’s Implementation of the Dummy Variable Model - p. 556 90. 11.5: Models with Dummy and Interval Variables - p. 558 91. 11.6: Extensions to Other Models - p. 570 92. 11.7: Estimating Linear Combinations of Regression Parameters - p. 570 93. 11.8: Weighted Least Squares - p. 574 94. 11.9: Correlated Errors - p. 577 95. 11.10: Chapter Summary - p. 581 96. 11.11: Chapter Exercises - p. 583 97. Chapter 12 Categorical Data - p. 597 98. Chapter 13 Special Types of Regression - p. 623 99. Chapter 14 Nonparametric Methods - p. 651 100. Appendix A Tables of Distributions - p. 685 101. Appendix B - p. 699 102. Appendix B A Brief Introduction to Matrices - p. 700.e1 103. Appendix C Descriptions of Data Sets - p. 701 104. Hints for Selected Exercises - p. 707 105. References - p. 741 106. Index - p. 747
