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Graduate-Level Statistics in Psychology

Nguồn ngoài

Graduate-Level Statistics in Psychology

By: Dr. Peter Ji, Adler University. Image: "Graduate-Level Statistics in Psychology Wordcloud" by D. Banks. CC-BY 4.0

Statistics
Tác giả
Peter Ji
Nhà xuất bản
Adler University
Nguồn
LibreTexts
Giấy phép
CC BY
Ngôn ngữ
EN
Danh mục
Khoa học cơ bản
Đọc trực tuyến Tải PDF (nguồn mở)
Mục lục· 100 mục
  1. 01: What is a Number
  2. 1.01: How to Start with Statistics
  3. 1.02: A Geek Out Explanation of Variation
  4. 1.03: Variations Lead to Numbers
  5. 1.04: The Battle of Words Versus Numbers
  6. 1.05: Quantifying a Construct or Why Numbers Are Better Than Words
  7. 1.06: Now You Love Numbers as Much as You Love the White Sox and Taylor Swift
  8. 1.07: Statistics Do Something with Numbers
  9. 1.08: Numbers Don't Lie but Numbers Don't Tell the Full Story
  10. 1.09: Seeing Numbers What I Want You to Learn
  11. 1.10: Connection Between Understanding How Things Vary and What You are Trying to Do
  12. 1.11: Discussion Questions
  13. 02: What are Statistics
  14. 2.01: Statistics Involves Comparison and Context
  15. 2.02: Statistics is About Finding Patterns
  16. 2.03: Statistics as Estimates or Making Guesses
  17. 2.04: Two Broad Categories of the Process of Using Statistics
  18. 2.05: Homework Questions
  19. 03: Variable Types
  20. 3.01: Variables - Not Always Obvious
  21. 3.02: How to Organize Variation With Variables
  22. 3.03: Categorical Variables- Variables That Vary by Type
  23. 3.04: Continuous Variables- Variables That Vary by Level
  24. 3.05: Nuances in Determining if a Variable Should be a Certain Type
  25. 3.06: Making Decisions About the Variables in Your Research Study
  26. 3.07: Lessons Learned About Variables
  27. 3.08: Homework Questions
  28. 04: Distributions
  29. 4.01: Distributions A Picture of Variation
  30. 4.02: Categorical Distributions
  31. 4.2.01: Evaluating the Plot
  32. 4.03: Reviewing Journal Articles for Frequency Distributions for Categorical Variables
  33. 4.04: Continuous Distributions
  34. 4.05: Evaluating the Quality of Frequency Distributions
  35. 4.06: Normal Distribution for Continuous Variables
  36. 4.07: Skewed Distribution- The Opposite of Normal Distribution
  37. 4.08: Evaluating a Continuous Distribution
  38. 4.09: Homework Questions
  39. 05: Measures of Central Tendency
  40. 5.01: What is Central Tendency Why Do We Use It
  41. 5.02: Three Types of Central Tendency and Why We Need Them
  42. 5.03: The Mean Median and Mode in Normal and Skewed Distributions
  43. 5.04: Homework Questions
  44. 06: Measures of Variability
  45. 6.01: What is Variance
  46. 6.02: How Do You Determine Variance
  47. 6.03: Partitioning of the Variance
  48. 6.04: Standardized Values of Reporting Scores
  49. 6.05: Homework Questions
  50. 07: Sampling Standard Error Central Limit Theorem
  51. 7.01: The Purpose of Sampling
  52. 7.02: Sampling from the Population
  53. 7.03: Getting a Good Sample - Get a Random Sample
  54. 7.04: Sampling Bias or Error
  55. 7.05: Central Limit Theorem (CLT) and Its Implications
  56. 7.06: Summary of Reasons Why You Need a Large Sample Size
  57. 7.07: Homework Questions
  58. 08: Probability Hypothesis Testing Type I and Type II Errors
  59. 8.01: The Role of Probability
  60. 8.02: Statistical Decision - Is a Result Significant or Not Significant
  61. 8.03: Hypotheses for Statistical Inference
  62. 8.04: How to Determine if a Result is Significant
  63. 8.05: Interpreting a Statistical Test Result
  64. 8.06: Testing a Hypothesis
  65. 8.07: How Do We Get the P Value for the Statistical Test
  66. 8.08: Confidence Intervals
  67. 8.09: Type I and Type II Errors
  68. 8.10: The Definition of Type I and Type II Errors
  69. 8.11: Discussion Questions
  70. 09: Effect Sizes and Power Analysis
  71. 9.01: Significant (P Value) Versus Meaningful (Effect Size) Results
  72. 9.02: What Are Effect Sizes
  73. 9.03: Statistical Power
  74. 9.04: How to Conduct a Power Analysis
  75. 9.05: Pause and Process Check Pulling P Values and Effect Sizes Together
  76. 9.06: Homework Questions
  77. 10: Introduction to Inferential Statistics
  78. 10.01: The Meaning of Inferential
  79. 10.02: Patterns
  80. 10.03: General Linear Model
  81. 10.04: Homework Questions
  82. 11: T-tests
  83. 11.01: When to Use the Independent T-test
  84. 11.02: Design Set Up
  85. 11.03: Commentary
  86. 11.04: T-test Assumptions
  87. 11.05: Reading T-tests
  88. 11.06: T-Tests You Need to Know for the Examination for Professional Practice in Psychology (EPPP) Licensing Exam
  89. 11.07: Reading Articles That Involve a T-test
  90. 11.08: Reading T-tests from Journal Articles
  91. 11.09: Summary
  92. 11.10: Discussion Questions
  93. 12: Analysis of Variance ANOVA
  94. 12.01: When to Use the ANOVA
  95. 12.02: The Concept Behind Analysis of Variance
  96. 12.03: - Interpreting the F-test and Post-Hoc Comparisons
  97. 12.04: Commentary
  98. 12.05: Reading Articles ANOVA
  99. 12.06: Summary
  100. 12.07: Homework Questions