Multiple Choice
Information was collected from employee records to determine whether there is an association between an employee's age and the number or workdays they miss. Excel results are summarized below:
From this printout you determine:
A) when tested at the 2% level of significance, there is no relationship between an employee's age and the number of days of work absences.
B) for each additional year of age, we can expect the number of days of absence to decrease by 0.2 days.
C) almost 67% of the variation in the number of absent days can be explained by the variation in the employee's ages.
D) when tested at the 2% level of significance, there is relationship between an employee's age and the number of days of work absences. For each additional year of age, we can expect the number of days of absence to decrease by 0.2 days.
E) when tested at the 2% level of significance, there is no relationship between an employee's age and the number of days of work absences. Almost 67% of the variation in the number of absent days can be explained by the variation in the employee's ages.
Correct Answer:

Verified
Correct Answer:
Verified
Q13: i. Correlation analysis is a group of
Q14: What is the variable used to predict
Q15: Based on the regression equation, we can<br>A)
Q16: A sales manager for an advertising agency
Q17: i. If the coefficient of correlation is
Q19: Assume the least squares equation is Y'
Q20: Given the following five points: (-2,0), (-1,0),
Q21: The following table shows the number of
Q22: i. The strength of the correlation between
Q23: i. If the coefficient of correlation is