Linear Regression

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

Model

Residuals vs Error

Predictions and Residuals in the Social Sciences

Covariance

Interpretations

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

Assumptions and Conditions

Relationship as Modeled, Not Observed!

Could Know

Model

Calculating Coefficients

Effect of Outliers

Root Mean Square Error (RMSQ)

Squared Error Regression Line

Interpretations

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

Assumptions

Using Residual Plots to Assess Assumptions

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