1. We consider the following regression models:
   • Model I (unrestricted model) Wage as a function of education level (1 variable: educ), gender (1 variable: female), location (3 variables: south, east, north), work experience (2 variables: experience, tenure). For a data of size n = 241, we found the following:
     1. SSR = 79227.2
     2. R-squared = 0.843516973171979
   • Model II Wage as a function of education level (1 variable: educ), location (3 variables: south, east, north), work experience (2 variables: experience, tenure). We found
     1. SSR = 82589.7
     2. R-squared = 0.836875640678729
   • Model III Wage as a function of education level (1 variable: educ), gender (1 variable: female), work experience (2 variables: experience, tenure). We found
     1. SSR = 81864.5
     2. R-squared = 0.838307995868054
   • Model IV Wage as a function of education level (1 variable: educ), gender (1 variable: female), location (3 variables: south, east, north). We found
     1. SSR = 81353.3
     2. R-squared = 0.839317675918775
   • Model V Wage as a function of education level (1 variable: educ), work experience (2 variables: experience, tenure). We found
     1. SSR = 81401.3
     2. R-squared = 0.83922287028021
   • Model VI Wage as a function of education level (1 variable: educ), location (3 variables: south, east, north). We found
     1. SSR = 81115.4
     2. R-squared = 0.839787556364915
   • Model VII Wage as a function of education level (1 variable: educ), gender (1 variable: female). We found
     1. SSR = 81695.6
     2. R-squared = 0.838641593208756 Calculate the F-statistic for the following hypothesis test: H0: the location variables and the work experience variables, together have no effect on wage. H1: H0 is not true. We reject the null hypothesis at the 5% level.

   Is this true or false?