PART 1: Descriptive Statistics__________________ __________________________5
Defining Important Terms_______________ ___________________________5
Data Analysis of Pay Rate________ _____________________________________6
Data Analysis of Pay Rate vs. Gender¬¬¬¬¬¬¬¬¬¬¬_______________________________________7
Data Analysis of Grade________________ ________________________________9
Data Analysis of Time within Grade_______________________________________11
PART 2: Regression Analysis____________________________________________ 12
Conclusion___________________________________________________________25 …show more content…
By simply looking at this graph we are able to see that the lower 25% of the salaries are much more agglomerated at the end and seem to all be in the same range. However, the salaries of those in the highest 25% of the data are much more spread out since the line is much longer at this end. The lines at the end of the box give a sense of how close together, or spread out our information is. In this case the higher salaries are more spread out.
Data Analysis of Pay Rate vs. Gender In the introduction we talked about the average salaries of men and women. We discussed how they were very much different even though we still had not taken into consideration the other variables given to us in the data set. Below we have created a box and whisker plot where the pay rate of the men and women of the company are put side by side in order to have a better idea of how they differ.
From the data displayed in the plots above we can see that there is a big difference between male and female salaries. The bottom 25% of the male employees make approximately the same amount as the women in the intermediate portion (from 25%-75%, middle 50%). Since this is a sample which we will base our whole population on, then we can say that this information pertaining to this sample represents our