The following estimated equations use the data in MLB 1 , which contains information on major league baseball salaries. The dependent variable, lsalary, is the log of salary. The two explanatory variables are years in the major leagues (years) and runs batted in per year (rbisyr): lsalary==n=lsalary=n=12.373+.1770years(.098)(.0132)353,SSR=326.196,SER=.964,R2=.33711.861+.0904years+.0302rbisyr(.084)(.0118)(.0020)353,SSR=198.475,SER=.753,R2=.597 (i) How many degrees of freedom are in each regression? Why is the SER smaller in the second regression than the first? (ii) The sample correlation coefficient between years and r bisyr is about 0.487. Does this make sense? What is the variance inflation factor (there is only one) for the slope coefficients in the multiple regression? Would you say there is little, moderate, or strong collinearity between years and rbisyr? (iii) How come the standard error for the coefficient on years in the multiple regression is lower than its counterpart in the simple regression? The following estimated equations use the data in MLB 1 , which contains information on major league baseball salaries. The dependent variable, lsalary, is the log of salary. The two explanatory variables are years in the major leagues (years) and runs batted in per year (rbisyr): lsalary==n=lsalary=n=12.373+.1770years(.098)(.0132)353,SSR=326.196,SER=.964,R2=.33711.861+.0904years+.0302rbisyr(.084)(.0118)(.0020)353,SSR=198.475,SER=.753,R2=.597 (i) How many degrees of freedom are in each regression? Why is the SER smaller in the second regression than the first? (ii) The sample correlation coefficient between years and r bisyr is about 0.487. Does this make sense? What is the variance inflation factor (there is only one) for the slope coefficients in the multiple regression? Would you say there is little, moderate, or strong collinearity between years and rbisyr? (iii) How come the standard error for the coefficient on years in the multiple regression is lower than its counterpart in the simple regression