Suppose that laurier company recently bought western company and subsequently te
ID: 3320633 • Letter: S
Question
Suppose that laurier company recently bought western company and subsequently terminated 20 of westerns employess. As a part of the buyout agreement it was promised that hthe severance packages offered to the former Western employees would be equivalent to those offered to laurier employees who had been terminated in the past year. 36 year old bill smith, a western employee for the past ten years, earning $32,000 a year was one of those let go. His severance package included an offer of 5 weeks severance pay. Bill claims this was less than what he should have gotten.
Given:
Weeks SP Age Years Pay
13 37 16 46
13 53 19 48
11 36 8 35
14 44 16 33
3 28 4 40
10 43 9 31
4 29 3 33
c) You would like to prepare a simple regression model to predict weeks of severance pay based upon only the number of years with the company.
First, conduct a simple linear regression of y on x to help test the theory that we can predict number of weeks of severance pay from number of years with the company.
Next, perform the appropriate two-tailed hypothesis test significance of the slope to see if a linear relationship exists between weeks of severance pay and years with the company. Your result is:
Reject the null; there is sufficient evidence that number of years with company may determine weeks of severance pay.
Do Not Reject the null; there is not sufficient evidence that number of years with company may determine weeks of severance pay.
Cannot be determined with only one independent variable.
none of the above
d) You would like to prepare a simple regression model to predict weeks of severance pay based upon only the number of years with the company.
First, conduct a simple linear regression of y on x to help test the theory that we can predict number of weeks of severance pay from number of years with the company.
Next, determine if the error variable, Epsilon, exhibits “constancy” of variance.
Your result is:
The error variable, Epsilon, does exhibit constancy, with only a few outliers.
The error variable, Epsilon, does not exhibit constancy; not even close!
The error variable, Epsilon, is too large and therefore an inference about its variance cannot be determined.
none of the above
.
a.Reject the null; there is sufficient evidence that number of years with company may determine weeks of severance pay.
b.Do Not Reject the null; there is not sufficient evidence that number of years with company may determine weeks of severance pay.
c.Cannot be determined with only one independent variable.
none of the above
d) You would like to prepare a simple regression model to predict weeks of severance pay based upon only the number of years with the company.
First, conduct a simple linear regression of y on x to help test the theory that we can predict number of weeks of severance pay from number of years with the company.
Next, determine if the error variable, Epsilon, exhibits “constancy” of variance.
Your result is:
a.The error variable, Epsilon, does exhibit constancy, with only a few outliers.
b.The error variable, Epsilon, does not exhibit constancy; not even close!
c.The error variable, Epsilon, is too large and therefore an inference about its variance cannot be determined.
d.none of the above
.
Explanation / Answer
c) You would like to prepare a simple regression model to predict weeks of severance pay based upon only the number of years with the company.
First, conduct a simple linear regression of y on x to help test the theory that we can predict number of weeks of severance pay from number of years with the company.
The regression equation is
Weeks Sp = 2.89 + 0.637 Years
Predictor Coef SE Coef T P
Constant 2.893 1.669 1.73 0.144
Years 0.6366 0.1367 4.66 0.006
S = 2.11600 R-Sq = 81.3% R-Sq(adj) = 77.5%
Next, perform the appropriate two-tailed hypothesis test significance of the slope to see if a linear relationship exists between weeks of severance pay and years with the company. Your result is:
a. Reject the null; there is sufficient evidence that number of years with company may determine weeks of severance pay.
d) You would like to prepare a simple regression model to predict weeks of severance pay based upon only the number of years with the company.
First, conduct a simple linear regression of y on x to help test the theory that we can predict number of weeks of severance pay from number of years with the company.
Test and CI for One Variance: RESI1
Method
Null hypothesis Sigma-squared = 4.477
Alternative hypothesis Sigma-squared not = 4.477
The chi-square method is only for the normal distribution.
The Bonett method is for any continuous distribution.
Statistics
Variable N StDev Variance
RESI1 7 1.93 3.73
95% Confidence Intervals
CI for CI for
Variable Method StDev Variance
RESI1 Chi-Square (1.24, 4.25) (1.55, 18.09)
Bonett (1.19, 4.35) (1.42, 18.90)
Tests
Test
Variable Method Statistic DF P-Value
RESI1 Chi-Square 5.00 6 0.913
Bonett — — 0.776
Next, determine if the error variable, Epsilon, exhibits “constancy” of variance.
Your result is:
a. The error variable, Epsilon, does exhibit constancy, with only a few outliers.
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