Statistics and Statistical Programming (Fall 2020)/w10 session plan

11/17 Agenda

• Revisiting confidence intervals for regression coefficients.
  • What precisely do they mean?
  • Can we use 1.96 x SE?
• If we flip the independent and dependent variables in a bivariate regression analysis: what does that tell us?
• Review exactly what we’re looking for in residual plots.
• (Optional thing Nick thought might be interesting) Everyone suggested a great number of factors our model might be missing (voting public’s perceptions of the economy, attributes of the candidates, effects of pandemic, etc.). How could we go about capturing these? Should we make a new linear regression model and post it on Twitter?