The Severance Pay for Laurier Employees - Case Study Example

All staff ought to know that the following factors are used to construct a linear regression model that has been used to predict the pay-off for laid-off workers. Using this model the pending appeal by one former Western employee will hopefully be determined.

Problem Definition:
We at Lauren sincerely regret the unavoidable employee lay-off situation that followed our acquisition of Western Company. We have received complaints from former Western employees who feel aggrieved by the amount of severance package we have stepped forward to offer our unfortunate brothers whose esteemed services were cut short at the firm for sustainability reasons. For demonstration, we shall pick the case of Bill Smith, a recently laid off Western employee, who we understand is concerned that Lauren is not genuine in the severance package offered to him. To clarify our stand, Lauren has hired the services of a statistician who worked out the figures contained in the analysis below regarding our severance packages policy.

Analysis:
Data were collected from a random sample of 50 former Lauren employees to ascertain whether Lauren has indeed been consistent in its award of severance packages. The points of the data include:
-Number of weeks of severance pay
-Age of employee
-Number of years with the company
-Annual pay (in thousands of dollars)

The output above shows the coefficients generated when the data from the randomly picked former Lauren employees is executed. We use the table values to construct a linear model that can be used to determine the amount of severance pay for any employee at the firm and emerging subsidiaries. The model is supposed to acquire the form:
y = β0 + β1x1 + β2x2 + β3x3 since we have got three independent variables; employees age at the time of termination of the contract, the length of time the employee has worked with us, and the annual pay of the employee. We have also one dependent variable, weeks of severance pay.
The coefficients (betas) for the function are:
β0 = 6.061; β1 = -0.008; β2 = 0.603; β3 = -0.070
We, therefore, come up with the following equation:
y = Number of weeks of severance pay
x1 = Age of employee with corresponding predicted constant β1
x2 = Number of years with the company with corresponding predicted constant β2
x3 = Annual pay (in thousands of dollars) with corresponding predicted constant β3
y = 6.061 - 0.008x1 + 0.603x2 – 0.070x3
This equation can further be made to absorb the variables in their crude word form.
Number of weeks of severance pay = 6.061 - 0.008 (Age of employee) + 0.603 (Number of years with the company) – 0.070 (Annual pay (in thousands of dollars))
Severance Pay Determination for Mr. Bill Smith:
We now apply the values of Mr. Smith’s employment to calculate the number of severance pay weeks he deserved. The following information is available about him:
Age = 36 years; annual pay = $ 32000; duration of employment = 10 years
y = 6.061 – 0.008 (36) + 0.603 ( 10) – 0.070 (32000)
= -2228.2 weeks

Therefore the different confidence intervals are:
Weeks SP: [9.3, 11.22]
Age: [37.94, 41.94]
Years of employment: [10.16, 12.96]
Pay: [33.56, 36.64]
The most important of the confidence interval values is the number of weeks of severance pay given to employees at the termination of their contracts.

Conclusions:
From the figure obtained above (-2228.2 weeks), it is clear that the model does not exactly obey the assumption that the pay period is directly related to any linear combination of the factors listed by Lauren as the determining factors of the pay period. This is a serious fact because it exposes Lauren as a company that does not honor or follow any pre-set procedures in the administration of the severance package.
The negative value indicates that Mr. Smith is supposed to work for the firm for another over 2220 weeks, a situation that depicts him as owing Lauren funds, to be recouped through his free services for this very long period. Read More