I'm reviewing the answer key that I was provided for my class on SAS JMP. I do not need help with understanding the logic behind the questions and answers, my goal is simply to learn how to recreate the answers in the attached document myself on SAS JMP in a step by step form that's easy for me to understand if possible.

I cannot attach the data file, but I have uploaded a screen shot in case it might help in providing my guidance.

My end goal is to be able to go through the assignment myself and be able to build the output in the answer key by myself.

JMP HO Equity - JMP Pro [2] 0 X File Tables File Edit Tables Rows Cols DOE Analyze Graph Tools View Window Help Recent File Equity D Info on Equity: Historical data gat BAD LOAN MORTDUE VALUE REASON JOB YOJ DEROG DELINQ CLAGE NINQ CLNO DEBTINC Filter (Ctri- Partition 1100 25860 39025 Homelmp Other 10.5 0 0 94.36667 9 Equity N 1300 70053 68400 Homelmp Other 7 0 2 121.8333 0 14 A 10 W 1500 13500 16700 Homelmp Other 0 0 149.4667 Columns (13/0) 4 1500 5 O 1700 97800 112000 Homelmp Office W 0 0 93.33333 0 14 Il. BAD 6 1700 30548 40320 Homelmp Other 0 0 101.466 8 37.11361 LOAN 1800 48649 57037 Homelmp Other un W N 77.1 17 O - MORTDUE 1800 28502 43034 Homelmp Other 11 0 88.76603 8 36.88489 VALUE 2000 32700 46740 Homelmp Other 3 IN 216.9333 12 O # I. REASON 10 2000 62250 Homelmp Sales 16 0 115.8 13 I. JOB YOU 11 2000 22608 18 DEROG 12 2000 20627 29800 Homelmp Office 11 o o . 1 122.5333 9 DELINQ 13 2000 45000 55000 Homelmp Other 3 0 86.06667 N 25 CLAGE 14 O 2000 64536 87400 Mgr 2.5 0 0 147.1333 0 24 NINQ CLNO 15 2100 71000 83850 Homelmp Other 8 0 123 O 16 16 2200 24280 34687 Homelmp Other 0 1 300.8667 0 8 DEBTINC 17 2200 90957 102600 Homelmp Mgr N 122.9 22 18 2200 23030 19 . 3.711312 Rows 19 2300 28192 40150 Homelmp Other 4.5 0 O 54.6 16 All rows 5,960 20 O 2300 102370 120953 Homelmp Office 2 0 0 90.99253 0 13 31.5885 Selected 2300 46200 Homelmp Other 14 Excluded 21 37626 0 1 122.2667 UT W OOOO Hidden 22 2400 50000 73395 Homelmp ProfExe 0 Labeled 23 2400 28000 40800 Homelmp Mgr 12 67.2 N 22 24 1 2400 18000 . Homelmp Mgr 22 2 121.7333 0 10Week 5 Exercises (Include screenshots in your responses when applicable) Book: Building Better Models with JMP Pro (Chapter 5) Use the Equity.jmp data from Blackboard for this exercise. This data set was first introduced in Week 2. Recall that the response variable is the variable BAD, where the value 1 indicates that the customer is a bad credit risk. a. Use functionality like the Columns Viewer, Distribution, Graph Builder, and Multivariate (Correlation) to re-familiarize yourself with this data. 1. Do any variables appear to be related to BAD? Explain in business language (it is not required to be technical in your response). Used Fit Y by X within JMP to look at relationships to BAD. All variables except CLNO show a significant relationship. do Logistic Fit of BAD By CLNO 1.00 0.75 BAD 0.50 0 25 0.00- 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 CLNO Iterations Whole Model Test Model LogLikelihood DF Chisquare Probo China Difference 0.0420 1 0.09930 0.7526 Full 2895.1050 2855.1546 (Students may provide more detail on their responses, but generally speaking, it should align to what is stated above)2. List any potential data quality issues you observe. There is no requirement to apply fixes. Only share your observations and possible recommendations. (Student responses will vary - ensure at least two data quality issues are cited for full credit) High correlation (0.8757) between VALUEand MORTDUE could indicate multicollinearity issue in the modeling Correlations LOAN MONIQUE VALLE DELING CLADE CINO DESTINC LOAN 1000 0.3354 0.10 J -AOIL MORTQUE 1 6000 01-0 0 1540 VALUE 1.0020 0 1713 YOU 0 1050 -0 0568 DELING 1.3000 D. 310 NINO 0 0-45 -0 0716 -0116 0 1413 DEBTTINC 0 0847 0.1540 0.1322 0.4534 D.1855 10900 Large number of missing values, especially DEBTINC. Summary Stathtia LILO0 HING Skewness and outliers Especially LOAN, MORTDUE, VALUE, YOJ, DEROG, DELINQ, CLAGE, NINQ. An example of data quality analysis on LOAN confirming skewness is highlighted below.b. Fit a logistic regression modelfor BAD, including all predictor variables. 1. What is the p-value for the whole model test? (Student results may vary slightly) 4 Whole Model Test Model -LogLikelihood DF ChiSquare Probs Chisq Difference 235.3036 16 470.6073