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Intro to Stats in the Social Sciences (MPC)

Nguồn ngoài

Intro to Stats in the Social Sciences (MPC)

Social Sciences
Tác giả
Adrianne Kotecki
Nhà xuất bản
Monterey Peninsula College
Nguồn
LibreTexts
Giấy phép
CC BY-NC
Ngôn ngữ
EN
Danh mục
Khoa học cơ bản
Đọc trực tuyến Tải PDF (nguồn mở)
Mục lục· 150 mục
  1. 01: An Introduction to Statistics
  2. 1.01: What are statistics
  3. 1.02: Why do we study statistics
  4. 1.03: Statistics in Psychology
  5. 1.04: Putting It Together- Types of Statistical Studies and Producing Data
  6. 1.05: Introduction to Psychological Measurement
  7. 1.06: Types of Data and How to Collect Them
  8. 1.07: Statistics and Science
  9. 1.08: How to Succeed in Statistics
  10. 1.09: Math Refresher
  11. 02: Describing Data using Distributions and Graphs
  12. 2.01: Introduction to Looking at Data (This is what too many numbers looks like)
  13. 2.02: Frequency Tables
  14. 2.03: Graphing Qualitative Variables- Bar Graphs
  15. 2.04: Graphing Qualitative Variables- Pie Charts
  16. 2.05: Graphing Quantitative Variables
  17. 2.06: Skew and Kurtosis
  18. 2.07: Graphing Quantitative Data- Line Graphs
  19. 2.08: Graphing Quantitative Data- Histograms
  20. 2.09: Graphing Quantitative Data- Boxplots
  21. 2.10: Graphing Quantitative Data- Scatterplots
  22. 2.11: Summary and Some Honesty
  23. 03: Measures of Central Tendency and Spread
  24. 3.01: What is Central Tendency
  25. 3.02: Measures of Central Tendency
  26. 3.03: Spread and Variability
  27. 3.E: Measures of Central Tendency and Spread (Exercises)
  28. 04: Z-scores and the Standard Normal Distribution
  29. 4.01: Normal Distributions
  30. 4.02: Introduction to z-scores
  31. 4.03: Calculating z-scores
  32. 4.04: Introduction to the z table
  33. 4.05: Z table of critical values
  34. 4.06: Predicting Amounts
  35. 4.07: Summary of z Scores
  36. 4.08: The Write-Up
  37. 05: Distributions
  38. 5.01: Introduction to Distributions
  39. 5.02: What is Probability
  40. 5.03: The Law of Large Numbers
  41. 5.04: Normal Distributions and Probability Distributions
  42. 5.05: Putting it All Together
  43. 5.06: Summary- The Bigger Picture
  44. 06: Inferential Statistics and an Introduction to Hypothesis Testing
  45. 6.01: Growth Mindset
  46. 6.02: People Samples and Populations
  47. 6.03: The Sampling Distribution of Sample Means
  48. 6.04: Using Standard Error for Probability
  49. 6.05: Sampling Distribution Probability and Inference
  50. 6.06: Logic and Purpose of Hypothesis Testing
  51. 6.07: The Probability Value
  52. 6.08: Descriptive versus Inferential Statistics
  53. 6.09: The Null Hypothesis
  54. 6.10: The Alternative Hypothesis
  55. 6.11: Null Hypothesis Significance Testing
  56. 6.12: Critical Values p-values and Significance
  57. 6.12.01: Critical Values
  58. 6.12.02: Summary of p-values and NHST
  59. 6.13: Steps of the Hypothesis Testing Process
  60. 6.14: Movie Popcorn
  61. 6.15: Effect Size
  62. 6.16: Office Temperature
  63. 6.17: The Two Errors in Null Hypothesis Significance Testing
  64. 6.17.01: Power and Sample Size
  65. 6.17.02: The p-value of a Test
  66. 07: Introducing t-tests (One-sample designs)
  67. 7.01: Introduction to One-Sample t-tests
  68. 7.02: Hypothesis Testing with t
  69. 7.03: Confidence Intervals
  70. 7.04: t table of critical values
  71. 7.05: Reporting Results
  72. 7.5.01: Descriptive and Inferential Calculations and Conclusion Example
  73. 08: Two Sample Designs
  74. 8.01: Repeated Measures
  75. 8.1.01: Change and Differences
  76. 8.1.02: Hypotheses of Change and Differences
  77. 8.1.03: Increasing Satisfaction at Work
  78. 8.1.04: Bad Press
  79. 8.02: Independent Samples
  80. 8.2.01: Difference of Means
  81. 8.2.02: Research Questions about Independent Means
  82. 8.2.03: Hypotheses and Decision Criteria
  83. 8.2.04: Independent Samples t-statistic
  84. 8.2.05: Standard Error and Pooled Variance
  85. 8.2.06: Movies and Mood
  86. 8.2.07: Effect Sizes and Confidence Intervals
  87. 8.2.08: Homogeneity of Variance
  88. 09: Analysis of Variance- Independent Samples
  89. 9.01: Why ANOVA
  90. 9.1.01: Observing and Interpreting Variability
  91. 9.1.02: Ratio of Variability
  92. 9.02: Introduction to ANOVA's Sum of Squares
  93. 9.2.01: Summary of ANOVA Summary Table
  94. 9.03: Hypotheses in ANOVA
  95. 9.04: Practice with Job Applicants
  96. 9.4.01: Table of Critical F-Scores
  97. 9.05: Introduction to Pairwise Comparisons
  98. 9.5.01: Pairwise Comparison Post Hoc Tests for Critical Values of Mean Differences
  99. 9.06: Practice on Mindset Data
  100. 9.07: On the Relationship Between ANOVA and the Student t Test
  101. 9.08: Non-Parametric Analysis Between Multiple Groups
  102. 10: Analysis of Variance- Repeated Measures
  103. 10.01: Introduction to Repeated Measures ANOVA
  104. 10.1.01: Things Worth Knowing About RM ANOVAs
  105. 10.02: ANOVA Summary Table
  106. 10.2.01: Repeated Measures ANOVA Sum of Squares Formulas
  107. 10.03: Practice with RM ANOVA Summary Table
  108. 10.3.01: Practice with Mindset
  109. 10.04: Non-Parametric RM ANOVA
  110. 11: Factorial ANOVA (Two-Way)
  111. 11.01: Introduction to Factorial Designs
  112. 11.1.01: Factorial Notations and Square Tables
  113. 11.02: Introduction to Main Effects and Interactions
  114. 11.2.01: Example with Main Effects and Interactions
  115. 11.2.02: Graphing Main Effects and Interactions
  116. 11.2.03: Interpreting Main Effects and Interactions in Graphs
  117. 11.2.04: Interpreting Interactions- Do Main Effects Matter
  118. 11.2.05: Interpreting Beyond 2x2 in Graphs
  119. 11.03: Two-Way ANOVA Summary Table
  120. 11.3.01: Calculating Sum of Squares for the Factorial ANOVA Summary Table
  121. 11.04: When Should You Conduct Post-Hoc Pairwise Comparisons
  122. 11.05: Practice with a 2x2 Factorial Design- Attention
  123. 11.5.01: Practice 2x3 Factorial ANOVA on Mindset
  124. 11.06: Choosing the Correct Analysis- Mean Comparison Edition
  125. 12: Correlation (and a little about Regression)
  126. 12.01: If something caused something else to change what would that look like
  127. 12.02: Pearsons r
  128. 12.03: Turning the numbers into a measure of co-variance
  129. 12.04: Examples with Data
  130. 12.05: Regression A mini intro
  131. 12.06: Interpreting Correlations
  132. 12.07: Summary
  133. 12.08: References
  134. 13: Chi-Square
  135. 13.01: Introduction to Chi-Square
  136. 13.1.01: Assumptions of the Test(s)
  137. 13.02: Introduction to Goodness-of-Fit Chi-Square
  138. 13.2.01: Critical Values of Chi-Square Table
  139. 13.2.02: Interpretation of the Chi-Square Goodness-of-Fit Test
  140. 13.03: Goodness of Fit Formula
  141. 13.04: Practice Goodness of Fit- Pineapple on Pizza
  142. 13.05: Introduction to Test of Independence
  143. 13.06: Practice Chi-Square Test of Independence- College Sports
  144. 13.6.01: Practice- Fast Food Meals
  145. 13.07: RM Chi-Square- The McNemar Test
  146. 13.08: Choosing the Correct Test- Chi-Square Edition
  147. 14: Wrapping it Up
  148. 14.01: Introduction to Wrapping Up
  149. 14.02: Choosing the Test
  150. 14.03: Why did you take this class