Social Statistics

  1. Bivariate Correlation and Regression
    1. Correlation Analysis
      1. Concept of Correlation
        1. Scatterplots
          1. Creating and Interpreting Scatterplots
            1. Identifying Patterns and Outliers
              1. Linear vs. Non-linear Relationships
              2. Pearson's Correlation Coefficient
                1. Assumptions
                  1. Calculation Methods
                    1. Interpretation of r Values
                      1. Statistical Significance Testing
                        1. Confidence Intervals for Correlations
                        2. Coefficient of Determination
                          1. r-squared Interpretation
                            1. Explained vs. Unexplained Variance
                            2. Spearman's Rank Correlation
                              1. When to Use
                                1. Calculation and Interpretation
                                2. Point-Biserial Correlation
                                  1. Correlation with Dichotomous Variables
                                  2. Partial Correlation
                                    1. Controlling for Third Variables
                                    2. Correlation vs. Causation
                                      1. Common Misconceptions
                                        1. Third Variable Problem
                                          1. Spurious Correlations
                                        2. Simple Linear Regression
                                          1. The Regression Model
                                            1. Population vs. Sample Regression
                                              1. Linear Relationship Assumption
                                              2. Least Squares Method
                                                1. Minimizing Sum of Squared Errors
                                                  1. Calculating Slope and Intercept
                                                  2. The Regression Equation
                                                    1. Interpreting the Intercept
                                                      1. Interpreting the Slope
                                                        1. Making Predictions
                                                        2. Assessing Model Fit
                                                          1. R-squared
                                                            1. Standard Error of Estimate
                                                              1. Residual Analysis
                                                              2. Assumptions of Linear Regression
                                                                1. Linearity
                                                                  1. Independence
                                                                    1. Homoscedasticity
                                                                      1. Normality of Residuals
                                                                      2. Inference in Regression
                                                                        1. Testing Significance of Slope
                                                                          1. Confidence Intervals for Parameters
                                                                            1. Prediction Intervals

                                                                        Previous

                                                                        11. Analysis of Categorical Data

                                                                        Go to top

                                                                        Next

                                                                        13. Multivariate Regression