A manufacturing firm wants to determine whether a relationship exists between the number of work-hours anemployee misses per year (Y) and the employee's annual wages (X), to test the hypothesis that increasedcompensation induces better work attendance. The regression output is provided below for a randomsample of employees from this organization.

1. How many employees were sampled?

2. At the 5% significance level, does this model indicate that there is a significant linear relationship between Annual Wages (X) and number of work-hours an employee misses per year (Y)?

A. No because the F ratio for the regression model with the variable annual wages has an p-value greater than ?.

B. No because the p-value for the constant is greater than ?.

C. Yes because ~9% of the variability in the number of work-hours an employee misses is explained by the annual salary.

D. No because 91% of the variation in Y remains unexplained. 91% is too high.

Multiple Adjusted StErr of R-Square Summary R R-Square Estimate 0.2976 0.0886 0.0185 116.2982 Degrees of Sum of Mean of F-Ratio p-Value ANOVA Table Freedom Explained 1 Squares 17085.2529 17085.2529 Squares 1.2632 0.2814 Unexplained 13 175828.4804 13525.2677 Standard Coefficient t-Value p-Value Regression Table Error Constant 218.3541 107.3929 2.0332 0.0630 Annual Wages -9.5775 8.5214 -1.1239 0.2814