A Director of Human Resources is exploring employee absenteeism at the INCOVA Hospital. A multiple linear regression analysis was performed using the following variables. The results are presented below. Variable Description Y number of days absent last fiscal year x1 commuting distance (in miles) x2 employee's age (in years) x3 length of employment at PPP (in years) Coefficients Standard Error t Statistic p-value Intercept 6.594146 3.273005 2.014707 0.047671 x1 -0.18019 0.141949 -1.26939 0.208391 x2 0.268156 0.260643 1.028828 0.307005 x3 -2.31068 0.962056 -2.40182 0.018896 R=0.498191 R2=0.248194 Adj R2=0.192089 se = 3.553858 n=73 !!
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
![A Director of Human Resources is exploring employee absenteeism at the INCOVA Hospital. A multiple linear regression analysis was performed
using the following variables. The results are presented below.
Variable
Description
Y
number of days absent last fiscal year
x1
commuting distance (in miles)
x2
employee's age (in years)
x3
length of employment at PPP (in years)
Coefficients Standard Error t Statistic p-value
Intercept 6.594146 3.273005
2.014707 0.047671
x1
-0.18019 0.141949
-1.26939 0.208391
x2
0.268156 0.260643
1.028828 0.307005
x3
-2.31068 0.962056
-2.40182 0.018896
R=0.498191
R2=0.248194 Adj R2=0.192089
se = 3.553858 n=73](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F0be2f49d-ed5c-4570-a16a-185f0ba38b02%2F6c48a121-f4e6-4f66-89f0-89d167f01d83%2Fg3lenno_processed.png&w=3840&q=75)
![For every additional year in the employee's age, the average number of absent days in the last year significantly (p-value<0.05) increases by
0.27 days.
For every additional year in employee's length of employment, the average number of absent days in the last year significantly (p-value<0.05)
decreases by 0.51 days.
None of the above is correct.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F0be2f49d-ed5c-4570-a16a-185f0ba38b02%2F6c48a121-f4e6-4f66-89f0-89d167f01d83%2F6h463ne_processed.png&w=3840&q=75)
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