代做data留学生、R设计代做、代写system、R编程语言代做

日期：2019-03-30 10:56

Assignment #4

Download the data from the following link. The data was obtained from Kaggle.

https://www.dropbox.com/sh/33f7zxx8ve6u0qk/AAC2RPmMy_iCiV_KTrW4D205a?dl=0

NOTE: This is not a team project. Do it by yourself. Submit your answers and the R-code used for your

analysis by Dec 18, 23:59PM. You can freely update your answer before the due. No late submission will be

accepted.

NOTE 2: Make your document formatted as follows: Times New Roman, 12-point font, double-spaced only

(not 1.5), 1-inch margins all around 8.5 x 11-inch paper (or A4), and the pages must be numbered. The

document should not exceed 10 pages including tables and figures. You can use a 10-point font and singlespace

for tables. The score will be determined not only by the accuracy and completeness of answers but also

by the presentation quality of the document (Do not simply screenshot the results of R output!)

Why are our best and most experienced employees leaving prematurely? Try to predict which valuable

employees will leave next. Fields in the dataset include:

Satisfaction Level

Last evaluation

Number of projects

Average monthly working hours

Time spent at the company (years)

Whether they have had a work accident

Whether they have had a promotion in the last 5 years

Departments (column sales)

Salary

Whether the employee has left

Q1. Load the data to your R system. How many variables and observations are in the data?

Q2. Generate the descriptive statistics for each variable.

Q3. Explore the relationships between variables. Can you find any interesting relationship?

Q4. Compare the employees who has left and who has remained. Visualize the comparison with a histogram

by factors.

Q5. Develop the best regression model to explain the employees leaving. Estimate the parameters of your

model. Can you find any meaningful result?

Q6. Develop the best classification model to predict the employees leaving. What is the sensitivity and the

specificity of your model?

Q7. What would you suggest the HR managers do to increase Satisfaction Level of employees? Conduct the

appropriate analysis to derive your suggestions.

Q8. Find other managerial insights from the data.

Q9. (Bonus question) Describe your efforts to be a Susan-like student for this course.