Mastering Data Analysis in Excel, week (1-6) All Quiz Answers with Assignments.

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 Mastering Data Analysis in Excel




week 6 Assignment :

PROMPT

What is your predictive model?

a. Describe the arithmetic clearly so that another learner could implement your model on new standardized input data if they wished.

b. Give an example of the score you would assign the following applicant, whether they would be approved or rejected for a credit card and why.

a) The first thing we must do is analyze the correlation of the variables, and identify which are the most relevant in the model. Then, we must identify the parameters or coefficients that will accompany the variables of said model, using the linear regression methodology in Excel seen in the course. The most relevant parametric values are: Years at a current employer: -0.19 income over the past year: -0.08 Current credit card debt: -0.19 Current automobile debt: -0.07 Then, with these coefficients and taking into account the correlation, we will make our model. Which is: SCORE = 0.19 * Years at a current employer -0.08 * income over the past year -0.19 * Current credit card debt-0.07 * Current automobile debt b)Considering that by optimizing AUC, we got the threshold for the minimum cost / event as 0.25. A score below -0.04 for example will be determined as a negative test, which translates as a financially profitable person, who could be approved for a credit card.




PROMPT

Give an example of the score you would assign the following applicant, whether they would be approved or rejected for a credit card and why.

b)Considering that by optimizing AUC, we got the threshold for the minimum cost / event as 0.25. A score below -0.04 for example will be determined as a negative test, which translates as a financially profitable person, who could be approved for a credit card.




PROMPT

What would the bank’s average profit per applicant be (net profits divided by 200) when using your predictive model on the Training Set?

Teniendo en cuenta de lo anterior, The net profit per applicant will be 794$ on the training set.




PROMPT

What is the incremental financial value per applicant of your model over no model on the Training Set?


the incremental financial value for application of the model on no model is $654.41




PROMPT

Evaluate your model on the Test Set data. How confident are you that your model does not over-fit the Training Set data? The only basis to evaluate over-fitting is to give the same metrics on the Test Set and Training Set, and compare them.


The model has a great performance in both data samples, since the correlation is well applied, and the parametric coefficients found are correct, this implies that the AUC is high and does not change considerably, in addition to maintaining the estimated costs per event.






Evaluate your model on the Test Set data. How confident are you that your model does not over-fit the Training Set data?

A. Choose between three broad degrees of confidence: “very” “somewhat” or “not at all.” (Note that “not at all” is still an acceptable answer if you give persuasive reasons for why you chose this answer).

B. Explain the evidence your degree of confidence is based upon. Your explanation should include the test set profits and training set profits per applicant.

How much confidence to have in the model must relate to the relationship between the profits-per-applicant on the Training Set and the Test Set

a) Very b) Because the AUC in both data samples is high and consistent, it is clear evidence of the efficiency of the model. In addition, it maintains a good estimated profit margin because the costs per event are not significantly altered.











































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