Introduction to Linear Regression
MUST KNOW
Model
Predicted Equation
Least Squared Errors
Interpretations
Interpreting Coefficients
Interpreting significance and insignificance
Interpreting the Intercept
Interpreting Coefficients for Quantitative IVs
Interpreting Coefficients for Qualitative IVs
Interpreting R2
Assumptions
Residual Plots
Linear Relationship
Should Know
Residuals vs Error
Predictions and Residuals in the Social Sciences
Covariance
Interpret Units
Qualitative IVs with more than two categories
Calculating Differences between Categories that Aren't the Reference
Substantively Interpreting Intercepts
Assessing Significance using Confidence Intervals
Standardized Quantitative Variables
Standardized Qualitative Variables
Assumptions and Conditions
Relationship as Modeled, Not Observed!
Could Know
Calculating Coefficients
Effect of Outliers
Root Mean Square Error (RMSQ)
Squared Error Regression Line
Inferences in Regression
Calculating T-Statistic
Calculating Confidence Intervals of the Slopes
Fitting non-linear relationships
Interpreting regressions with non-linear terms
Polynomials
Log-Linear Model
Using Residual Plots to Assess Assumptions