A company wants to study the effect of an employee's length of employment on their number of workdays absent. The company collected the following information on a random sample of seven employees, and analyzed the relationship by using linear regression model with outputs as follows, Number of Workdays About 1 3 3 5 7 7 8 Length of Employment (very) $6 9 42 20 Regression Statistics Multiple R 0.863506052 R Square 0.745642702 Adjusted R Square 0.694771242 Standard Error 1.315153843 Observations ANOVA df SS MS F Significance F Regression 25.35185185 25.3518519 14.65739 0.012266146 Residual Total aur 8.648148148 1.72962963 34 Coefficients Standard Error It stat -value Intercept 7.740740741 0.871534738 8.88173517 01000301 length of employment -0.68518519 0.178969769 -3.8284968 0.017260 What is the meaning of "R square = 0.7456" as indicated in the output above? 74.56% of the variation of number of workdays absent can be explained by t of employment 74.56% of the variation of the length of employment can be explained by the number workdays absent )The correlation between the number of workdays absent and the length of employment is 0.7456 The association between the number of workdays absent and the length of employment is 0.7456 W 26 P 3 2