Home

  1. Introduction
  2. Graphing Distributions
  3. Summarizing Distributions
  4. Describing Bivariate Data
  5. Probability
  6. Research Design
  7. Normal Distribution
  8. Advanced Graphs
  9. Sampling Distributions
  10. Estimation
  11. Logic of Hypothesis Testing
  12. Tests of Means
  13. Power

  14. Regression
    1. Contents
      Standard
    2. Introduction to Linear Regression
      Standard         Video
    3. Linear Fit Demo
      Standard
    4. Partitioning Sums of Squares
      Standard   Video
    5. Standard Error of the Estimate
      Standard         Video
    6. Inferential Statistics for b and r
      Standard         Video
    7. Influential Observations
      Standard         Video
    8. Regression Toward the Mean
      Standard         Video
    9. Introduction to Multiple Regression
      Standard         Video
    10. Statistical Literacy
      Standard
    11. Exercises
      Standard

  15. Analysis of Variance
  16. Transformations
  17. Chi Square
  18. Distribution Free Tests
  19. Effect Size
  20. Case Studies
  21. Calculators
  22. Glossary
 
Learning Objectives
  1. Compute the sum of squares Y
  2. Convert raw scores to deviation scores
  3. Compute predicted scores from a regression equation
  4. Partition sum of squares Y into sum of squares predicted and sum of squares error
  5. Define r2 in terms of sum of squares explained and sum of squares Y.

Audio by Alex Shabad