HOURS WAGES 49 12.8 36 14.5 127 8.3 91 10.2 72 10.0 34 11.5 155 8.8 11 17.2 191 7.8 6 15.8 63 10.8 79 9.7 543 12.1 57 21.2 82 10.9 A large manufacturing firm wants to determine whether a relationship exists between y, the number of work-hours an employee misses per year, and x, the employee’s annual wages. A sample of 15 employees produced the data in the accompanying data set (MISSWORK). Fit the first order model E(y)=β0+β1x, to the data. (already solved) Check model assumptions. What do you notice in the residual vs fitted plot? (already solved) After searching through its employees’ files, the firm has found that employee #13 had been fired but his name had not been removed from the active employee payroll. This explains the large accumulation of work-hours missed (543) by that employee. In view of this fact, what is your recommendation concerning this outlier? (already solved) Measure how influential the observation for employee #13 is on the regression analysis. Refit the model to the data, excluding this observation, and compare the results to those in part a). ** Question 1,2,3 already done. Please solve the last question (4)
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.
HOURS WAGES
49 12.8
36 14.5
127 8.3
91 10.2
72 10.0
34 11.5
155 8.8
11 17.2
191 7.8
6 15.8
63 10.8
79 9.7
543 12.1
57 21.2
82 10.9
A large manufacturing firm wants to determine whether a relationship exists between y, the number of work-hours an employee misses per year, and x, the employee’s annual wages. A sample of 15 employees produced the data in the accompanying data set (MISSWORK).
- Fit the first order model E(y)=β0+β1x, to the data. (already solved)
- Check model assumptions. What do you notice in the residual vs fitted plot? (already solved)
- After searching through its employees’ files, the firm has found that employee #13 had been fired but his name had not been removed from the active employee payroll. This explains the large accumulation of work-hours missed (543) by that employee. In view of this fact, what is your recommendation concerning this outlier? (already solved)
- Measure how influential the observation for employee #13 is on the
regression analysis . Refit the model to the data, excluding this observation, and compare the results to those in part a).
** Question 1,2,3 already done. Please solve the last question (4)
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