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Business Intelligence Methods: Logistic Regression and Analysis of your choice

Your task: Run a logistic regression. Using the output answer the following:

(I got the output by using the program SSPS, I put it in a different file)

 

1) What is the probability of admission for a student who came from a rank 2 institution with a 750 GRE and a GPA of 3.33?

Solution:

P(Y) = Exp(α + β1X1 + β2X2 + … βnXn)/ [1+ Exp(α + β1X1 + β2X2 + … βnXn)]

P(Admission) = Exp(α + β1X1 + β2X2 + … βnXn)/ [1+ Exp(α + β1X1 + β2X2 + … βnXn)]

P(Admission) = Exp(-3.45 -.56*2 + .777*3.33 + .002*750)/ [1+ Exp(-3.45 -.56*2 + .777*3.33 + .002*750)] = .38

So P(Admission| rank=2, GPA =3.33, GRE = 750) = .38

 

What is the probability of admission for a student with an 800 GRE, 3.11 GPA and a Rank 3 school?

 

 

 

 

 

2) Select at random 10 individuals. Calculate the probability of admission for each.

 

 

 

3) Using the criteria p(admission) > .5 predicts admission, please create a classification matrix for the ten observations you choose.

Ex: if we observed a student who had a 750 GRE, 3.33 GPA, and Rank “2” who was admitted, that student would be an “false negative”, that is we predicted she would not have been admitted (p= .38, which is less than .5), when in fact she was admitted. How many of your 10 observations were classified correctly?

 

Part II: Analysis of your choice

Run an analysis of the data with a cluster analysis, association rule, or classification technique of your choice. (By using Weka) (I have done the lab part, I got the output of the classification technique using J48 from the program Weka, I put it in a different file) (I didn’t choose the association rule because Weka didn’t allow me to do it because it is hard to find the data, so that is why I chose to do the classification technique)

1) Outline briefly a research question/business issue you are investigating.

2) Provide a brief overview of what technique you chose to investigate.

3) Analyze the results: describe two or more leaves, clusters, or rules in detail.

4) Describe the insights you gained form the model, and any recommendations or interesting findings you came away with.

 

 

How to use Weka:

  • Open the program
  • Click on Explorer
  • Open file
  • Files of type: choose (csv), and then choose the excel file
  • Click on Classify => choose => trees => J48 => start:- now you can see the output of J48 design tree

 

use version weka-3-6-10jre-x64.exe

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Important notes;

  • It must be written in a very simple language by using only very simple and Basic English words. So I don’t want it to be like professional writing, I want it to be like a first year student college writing level by using simple and basic words.
  • I have uploaded the excel file (data).
  • You cannot use other than SSPS for the first part and Weka for the second part, you can however do the calculation by the excel or by hand.
  • I have already done all the lab parts, the SSPS and Weka, so you don’t have to do them just look at the output, or you can do them to see them in a better view!
  • Please see the next page!

 

 

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