The accompanying file contains historical data for 400 customers related to automobile loans. The information includes whether the customer defaulted on the loan (Default = 1 for default, 0 otherwise) and the corresponding loan-to-value ratio (LTV in %), FICO credit score (FICO), and customer age.
a. Estimate the logistic regression model to find the probability and odds of default given LTV = 70, FICO = 600, and Age = 50.
b. Find the corresponding probability and odds if FICO = 700.
c. Interpret the percentage change in the default odds when each predictor variable increases by one unit, holding the other variables constant.

 

Default	LTV	FICO	Age
0	70.50	705	61
0	73.91	586	20
0	80.33	779	67
0	91.06	764	55
0	68.45	776	32
0	90.75	721	52
1	92.23	633	35
0	83.15	735	65
1	82.13	543	35
0	63.98	775	20
0	68.59	788	36
0	67.65	629	37
0	83.98	727	36
0	74.29	738	66
0	86.63	716	37
1	77.93	659	45
1	84.96	664	64
0	93.74	617	64
0	74.16	714	30
0	86.88	746	54
0	91.91	649	35
0	68.79	669	46
0	82.85	706	55
0	66.02	576	59
0	70.55	626	61
0	74.36	641	20
0	62.43	561	29
0	74.24	773	36
1	89.83	750	33