Examine each model, given the definitions of each of the variables, and see if you can accurately interpret, in words, each of the regression coefficients (intercept and slope). When you have formulated the best interpretation you can come up with, move the cursor over the highlighted coefficients and see if your interpretation matches the "official" one.

Model 1a: ARG_i = b₁ + b₂ AGEDIFF_i + e_i

where ARG_i = average weekly number of arguments between heterosexual couple i

      AGEDIFF_i = absolute difference in age between members of couple i

Model 1b: ARG_i = b₁ + b₂ AGEDIFF_i + b₃ AGEMALE_i + e_i

 where AGEMALE_i = age of the male partner in heterosexual couple i

 Model 1c: ARG_i = b₁ + b₂ AGEDIFF_i + b₃ AGEMALE_i + b₄ AGEFEM_i + e_i

 where AGEFEM_i = age of the female partner in heterosexual couple i

CAUTION: Model 1c will fail if the male is always older than the female in your sample. Why?

Model 2a: TRIPS_i = b₁ + b₂ DIST_i + e_i

where TRIPS_i = number of recreational trips to Lake Wobegon by person i

      DIST_i = distance from home to Lake Wobegon for person i

Model 2b: TRIPS_i = b₁ + b₂ DIST_i + b₃ AGE_i + e_i

 where AGE_i = age of person i

 Model 2c: TRIPS_i = b₁ + b₂ DIST_i + b₃ AGE_i + b₄ BOATS_i + e_i

 where BOATS_i = number of boats owned by person i

Model 2d: TRIPS_i = b₁ + b₂ DIST_i + b₃ AGE_i + b₄ BOATS_i + b₅ KIDS_i + e_i

 where KIDS_i = number of children in the household of person i