Phu Xuan University Library
|
PXU E-LIB
Sign in
Answering Questions with Data - Introductory Statistics for Psychology Students

External

Answering Questions with Data - Introductory Statistics for Psychology Students

This is a free textbook teaching introductory statistics for undergraduates in Psychology. This textbook is part of a larger OER course package for teaching undergraduate statistics in Psychology, including this textbook, a lab manual, and a course website. All of the materials are free and copiable, with source code maintained in Github repositories.

Applied StatisticsStatistics
Author
Matthew J. C. Crump
Publisher
Brooklyn College of CUNY
Source
LibreTexts
License
CC BY-SA
Language
EN
Category
Information Technology
Read online Download PDF (open licence)
Contents· 119 sections
  1. 01: Why Statistics
  2. 1.01: On the Psychology of Statistics
  3. 1.02: The cautionary tale of Simpsons paradox
  4. 1.03: Statistics in Psychology
  5. 1.04: Statistics in Everyday Life
  6. 1.05: Theres More to Research Methods than Statistics
  7. 1.06: A brief Introduction to Research Design
  8. 1.07: Introduction to Psychological Measurement
  9. 1.08: Scales of measurement
  10. 1.09: Assessing the Reliability of a Measurement
  11. 1.10: The role of variables predictors and outcomes
  12. 1.11: Experimental and non-experimental research
  13. 1.12: Assessing the validity of a study
  14. 1.13: Confounds Artifacts and other Threats to Validity
  15. 1.14: Summary
  16. 1.15: Videos
  17. 1.16: References
  18. 02: Describing Data
  19. 2.01: This is what too many numbers looks like
  20. 2.02: Look at the data
  21. 2.03: Important Ideas - Distribution Central Tendency and Variance
  22. 2.04: Measures of Central Tendency (Sameness)
  23. 2.05: Measures of Variation (Differentness)
  24. 2.06: Using Descriptive Statistics with data
  25. 2.07: Rolling your own descriptive statistics
  26. 2.08: Remember to look at your data
  27. 2.09: Videos
  28. 2.10: References
  29. 03: Correlation
  30. 3.01: If something caused something else to change what would that look like
  31. 3.02: Pearsons r
  32. 3.03: Turning the numbers into a measure of co-variance
  33. 3.04: Examples with Data
  34. 3.05: Regression A mini intro
  35. 3.06: Interpreting Correlations
  36. 3.07: Summary
  37. New Page
  38. 04: Probability Sampling and Estimation
  39. 4.00: Prelude to Probability Sampling and Estimation
  40. 4.01: How are Probability and Statistics Different
  41. 4.02: What Does Probability Mean
  42. 4.03: Basic Probability Theory
  43. 4.04: The Binomial Distribution
  44. 4.05: The normal distribution
  45. 4.06: Other useful distributions
  46. 4.07: Summary of Probability
  47. 4.08: Samples populations and sampling
  48. 4.09: The Law of Large Numbers
  49. 4.10: Sampling distributions and the central limit theorem
  50. 4.11: The Central Limit Theorem
  51. 4.12: z-scores
  52. 4.13: Estimating population parameters
  53. 4.14: Estimating a confidence interval
  54. 4.15: Summary
  55. 4.16: Videos
  56. 4.17: References
  57. 05: Foundations for inference
  58. 5.01: Brief review of Experiments
  59. 5.02: The data came from a distribution
  60. 5.03: Is there a difference
  61. 5.04: Chance makes some differences more likely than others
  62. 5.05: The Crump Test
  63. 5.06: The randomization test (permutation test)
  64. 5.07: Videos
  65. 06: t-Tests
  66. 6.00: Prelude to t-Tests
  67. 6.01: Check your confidence in your mean
  68. 6.02: One-sample t-test A new t-test
  69. 6.03: Paired-samples t-test
  70. 6.04: The paired samples t-test strikes back
  71. 6.05: Independent samples t-test The return of the t-test
  72. 6.06: Simulating data for t-tests
  73. 6.07: Videos
  74. 6.08: References
  75. 07: ANOVA
  76. 7.01: ANOVA is Analysis of Variance
  77. 7.02: One-factor ANOVA
  78. 7.03: What does F mean
  79. 7.04: ANOVA on Real Data
  80. 7.05: ANOVA Summmary
  81. 7.06: References
  82. 08: Repeated Measures ANOVA
  83. 8.01: Repeated Measures Design
  84. 8.02: Partioning the Sums of Squares
  85. 8.03: Calculating the RM ANOVA
  86. 8.04: Things worth knowing
  87. 8.05: Real Data
  88. 8.06: Summary
  89. 8.07: References
  90. 09: Factorial ANOVA
  91. 9.00: Prelude to Factorial ANOVA
  92. 9.01: Factorial Basics
  93. 9.02: Purpose of Factorial Designs
  94. 9.03: Graphing the means
  95. 9.04: Knowing what you want to find out
  96. 9.05: Simple analysis of 2x2 repeated measures design
  97. 9.06: 2x2 Between-subjects ANOVA
  98. 9.07: Fireside chat
  99. 9.08: Real Data
  100. 9.09: Factorial summary
  101. New Page
  102. 10: More On Factorial Designs
  103. 10.01: Looking at main effects and interactions
  104. 10.02: Interpreting main effects and interactions
  105. 10.03: Mixed Designs
  106. 10.04: More complicated designs
  107. 11: Simulating Data
  108. 11.01: Reasons to simulate
  109. 11.02: Simulation overview
  110. 11.03: Simulating t-tests
  111. 11.04: Simulating one-factor ANOVAs
  112. 11.05: Other resources
  113. 12: Thinking about Answering Questions with Data
  114. 12.01: Effect-size and power
  115. 12.02: Power
  116. 12.03: Planning your design
  117. 12.04: Some considerations
  118. New Page
  119. New Page