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  • 0.1 Course introduction (14.22)
  • 1.1 Experimental research - Example 1 Polio vaccine (11.17)
  • 1.2 Experimental research - Example 2 Memory training (16.21)
  • 1.3 Experimental research - Example 3 The concept of random (6.27)
  • 2.1 Correlational research - Example 1 Personality (9.07)
  • 2.2 Correlational research - Example 2 Intelligence (9.09)
  • 2.3 Correlational research - Example 3 Sports-related concussion (11.24)
  • 3.1 Variables and distributions - Types of variables (14.53)_x264
  • 3.2 Variables and distributions - Distributions_Histograms (22_39)_x264
  • 3.3 Variables and distributions - Scales of measurement (6.46)_x264
  • 4.1 Summary statistics - Measures of central tendency (15.22)_x264
  • 4.2 Summary statistics - Measures of variability (17.01)_x264
  • 5.1 Correlation - Overview (15.58)_x264
  • 5.2 Correlation - Calculation of R (15.29)_x264
  • 5.3 Correlation - Assumptions (12.13)_x264
  • 6.1 Measurement - Reliability (14.31)
  • 6.2 Measurement - Validity (9.50)
  • 6.3 Measurement - Sampling (11.03)
  • 7.1 Introduction to regression - Overview (19.02)
  • 7.2 Introduction to regression - Calculation of regression coefficients (8.22)
  • 7.3 Introduction to regression - Assumptions (7.34)
  • 8.1 Null Hypothesis Significance Tests (NHST) - Overview (17.05)
  • 8.2 Null Hypothesis Significance Tests (NHST) - Problems & remedies (15.55)
  • 9.1 Central limit theorem - Sampling distributions (11.51)
  • 9.2 Central limit theorem - The central limit theorem (14.16)
  • 10.1 Confidence intervals - Confidence intervals for sample means (18.19)
  • 10.2 Confidence intervals - Confidence intervals for regression coefficients (10
  • 11.1 Multiple regression - Multiple regression (15.28)
  • 11.2 Multiple regression - Matrix algebra (14.50)
  • 11.3 Multiple regression - Estimation of coefficients (9.34)
  • 12.1 Multiple regression continued - The general linear model (7.55)
  • 12.2 Multiple regression continued - Dummy coding (12.24)
  • 13.1 Moderation - Example 1 (27.13)
  • 13.2 Moderation - Centering predictors (15.15)
  • 13.3 Moderation - Example 2 (6.44)
  • 14.1 Mediation - Standard approach (18.33)
  • 14.2 Mediation - Path analysis (14.41)
  • 15.1 Group comparisons (t-tests) - Introduction (14.12)
  • 15.2 Group comparisons (t-tests) - Dependent t-tests (12.48)
  • 15.3 Group comparisons (t-tests) - Independent t-tests (18.50)
  • 16.1 Group comparisons (ANOVA) - One-way ANOVA (22.17)
  • 16.2 Group comparisons (ANOVA) - Post-hoc tests (7.35)
  • 17.1 Factorial ANOVA - Factorial ANOVA (16.37)
  • 17.2 Factorial ANOVA - Example (8.43)
  • 18.1 Repeated measures ANOVA - Repeated measures_ Pros and cons (21.33)
  • 18.2 Repeated measures ANOVA - Repeated measures ANOVA example (11.36)
  • 19.1 Chi-square - Chi-square goodness of fit (11.27)
  • 19.2 Chi-square - Chi-square test of independence (10.07)
  • 20.1 Binary logistic regression - Overview (12.15)
  • 20.2 Binary logistic regression - Example (11.57)
  • 21.1 Assumptions revisited (correlation and regression) - Assumptions (12.36)
  • 21.2 Assumptions revisited (correlation and regression) - Transformations (6.37)
  • 22.1 Generalized Linear Model - Parametric vs. non-parametric statistics (10.22)
  • 22.2 Generalized Linear Model - Examples (14.28)
  • 23.1 Assumptions revisited (t-tests and ANOVA) - Overview (8.32)
  • 23.2 Assumptions revisited (t-tests and ANOVA) - Examples (10.21)
  • 24.1 Non-parametrics - Research methods and descriptive statistics (5.32)
  • 24.2 Non-parametrics - Simple and multiple regression (7.42)
  • 24.3 Non-parametrics - Group comparisons t-tests and ANOVA (5.52)
  • 24.4 Non-parametrics - Procedures for non-normal distributions and non-linear mo
  • 25.1 Lab 1 - Introduction to R (12.03)
  • 25.2 Lab 2 - Histograms and summary statistics (37.04)
  • 25.3 Lab 3 - Scatterplots and correlations (20.46)
  • 25.4 Lab 4 - Regression (28.33)
  • 25.5 Lab 5 - Confidence intervals (30.10)
  • 25.6 Lab 6 - Multiple regression (21.45)
  • 25.7 Lab 7 - Moderation and mediation (15.48)
  • 25.8 Lab 8 - Group comparisons (18.18)
  • 25.9 Lab 9 - Factorial ANOVA (12.16)
  • 25.10 Lab 10 - Binary logistic regression (18_56)
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