Interpret the slope coefficient for wage based on this MLR model.
Contingency Table
A contingency table can be defined as the visual representation of the relationship between two or more categorical variables that can be evaluated and registered. It is a categorical version of the scatterplot, which is used to investigate the linear relationship between two variables. A contingency table is indeed a type of frequency distribution table that displays two variables at the same time.
Binomial Distribution
Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.
Absenteeism: Absenteeism can be a serious employment problem. It is estimated that absenteeism reduces potential output by more than 10%. Two economists launched a research project to learn more about the problem. They randomly selected 100 organizations to participate in a 1-year study. For each organization, they recorded the average number of days absent per employee and several variables thought to affect absenteeism. The file ‘absenteeism FinEx’ contains the data on these selected 100 organizations.
Clearly write the linear regression equation below without using X’s and Y’s.
Interpret the slope coefficient for wage based on this MLR model.
![Column 1, Wage:
Average employee wage
Column 2, Pct PT:
Percentage of part-time employees
Column 3, Pct U :
Percentage of unionized employees
Column 4: Av Shift : Availability of shiftwork
1= Yes
0 = No
Column 5: U/M Rel : Union-management relationship
1= good 0 = Not good
Column 6: Absent: Average number of days absent per employee](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Faa05795a-07ea-44b9-a83e-44b537f56ea9%2F23082a54-393d-4da7-87f1-7b687ee2cbda%2F9el8ah_processed.png&w=3840&q=75)
![Regression Analysis:
The regression equation is
Absent = 10.3 - 0.000203 Wage - 0.107 Pct PT + 0.0599 Pct U + 1.56 Av Shift
- 2.64 UM Rel
Predictor
Coef
SE Coef
P
Constant
10.265
1.172
8.76 0.000
Wage
-0.00020330 0.00003573 -5.69 0.000
Pct PT
-0.10687
0.02949 -3.62 0.000
Pct U
0.05985
0.01240
4.83 0.000
Av Shift
1.5619
0.5027
3.11 0.002
UM Rel
-2.6366
0.4922 -5.36 0.000
S = 2.35589
R-Sq = 53.2%
R-Sq (adj) = 50.78
Analysis of Variance
Source
DF
MS
F
P
Regression
5
593.90 118.78 21.40 0.000
Residual Error 94
521.72
5.55
Total
99
1115.62](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Faa05795a-07ea-44b9-a83e-44b537f56ea9%2F23082a54-393d-4da7-87f1-7b687ee2cbda%2F628v1l_processed.png&w=3840&q=75)
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