Part 2- Stats report

To determine whether Bill is correct in his assessment of the severance package, the stultification needs to find the relationships between the number of weeks of severance pay and the number of years with the company.

Describe the variables included in the case.

Here the Number of weeks of severance pay is a dependent variable (Y) and Number of years with the company is the independent variable (X)

The descriptive summary of the data is given below:

The average value of the Week SP is 10.26 and Average years is 11.56, while the standard deviation of the Weeks SP is 3.41 and Standard Deviation is 4.93. The data is normally distributed because the skewness of the data is between -2 and 2 and there is no outlier found in the data

The scatter Plot:

The data show an uphill pattern as the years move from left to right, this indicates a positive relationship between X and Y. As the X-values increase (move right), the Y-values tend to increase (move up). It shows a there strong positive relationship between Number of weeks of severance pay is dependent variable (Y) and Number of years with the company is independent variable (X)

Regression output:

The regression equation:

So, we see that the R-squared value is = 0.6903. It means that the independent variables are able to explain only 69.03% of the variation in the dependent variable. So, this is a good model to be used to predict the values of the Number of weeks of severance pay.

We can see that the required value of the F-statistic is = 106.997 and the p-value is 0.000000' so, the value of the p-value indicates that the null hypothesis will be rejected at any level of significance (generally 0.05 or 0.01) because the p-value is very smaller than the significance level so the model is significant.

References

George, D., & Mallery, P. (2014). IBM SPSS statistics 21 step by step: A simple guide

and reference(13th ed.). Boston, MA: Pearson. ISBN: 9780205985517

Warner, R. M. (2013). Applied statistics: From bivariate through multivariate techniques (2nd ed.). Thousand Oaks, CA: Sage.