Attrition Analysis ( Datascience with SAS)

Discussion in 'Big Data and Analytics' started by _26245, Dec 6, 2018.

  1. _26245

    _26245 Member

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    Hi Priyanka,

    I am working on Employee Attrition Analysis project. Can I use proc Logistic to check Max and Min values for the probability of churn. Also, what analysis can I determine using Proc Univariate . I need help with the last two points.

    Here is my code:

    title 'Stepwise Regression on the probability of churn';

    proc logistic data=work.attrition outest=betas covout ;

    MODEL Retain_Indicator (event='1') = Sex_Indicator Relocation_Indicator Marital_Status

    / selection=stepwise

    slentry=0.4

    slstay=0.45

    details

    lackfit;

    Output out = outdata p=PREDICTED lower=LCL upper= UCL;


    RUN;


    PROC UNIVARIATE DATA = WORK.Attrition;

    VAR Retain_Indicator;

    Histogram Retain_Indicator/Normal;

    RUN;
     
    #1
  2. Priyanka_Mehta

    Priyanka_Mehta Well-Known Member
    Simplilearn Support

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    Hi, Good effort in resolving the problem statement..

    I would liek to inform you that, definitely you can use the Logistic regression to find out the min and max probability of churn. I am sure you are referring to a mentoring session where we have discussed the same. So just to notify you again that always remember, there are many ways to achieve a particular task and being a data scientist, you should always explore different ways to do the analysis.

    Now regarding, Univariate, it is used to request a variety of statistics for summarizing the data distribution of each analysis variable: It is used to do descriptive statistics for multiple variables. I hope this will help you.
     
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  3. _26245

    _26245 Member

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    Thanks Priyanka. this is helpful. Will get back to you if i have more questions.
     
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  4. Priyanka_Mehta

    Priyanka_Mehta Well-Known Member
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    Sure, Anytime.

    All the very best for your Project and Course completion.
     
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  5. _26245

    _26245 Member

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    Hi Priyanka,

    I am working on Attrition Analysis project. the p value of all the variables are greater than 0.05 hence not Significant . in that case are we suppose to drop all variables from the model.

    Thanks for your time and help.
     
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