1. Provide the summary statistic as well as histograms for the variables balance and income for the whole dataset. Explain some of the key characteristics of the dataset.
2. Using conditional statements on the variables default and student, provide the summary statistics (as well as histograms) for the variables balance and income for the different combinations of groups. That is, (1) default = Yes and student = Yes; (2) default = Yes, student = No; (3) default = No, student = Yes; and (4) default = No, student =No. Explain some of the key characteristics of the dataset.
3. Using the variable default as the response variable, fit a logistic regression model with the predictor variables student, balance, and income. Comment on the output. What can you say about the significance of the predictor variables? How good is the model fit?
4. Let's assume a credit card applicant is a student with a balance of $621 and an income of $1850. How likely will he/she default according to the fitted logistic regression model? Explain and show calculations.

default	student	balance	income
Yes	Yes	2205.8	14271.49
Yes	Yes	1774.694	20359.51
Yes	No	1889.599	48956.17
Yes	No	1763.579	46227.07
Yes	No	1531.716	43930.4
Yes	No	780.1726	51656.87
No	No	825.5133	24905.23
No	No	1161.058	37468.53
No	No	0	29275.27
No	Yes	0	13760.3
No	Yes	927.8877	22473.38
No	Yes	1390.031	21299.1
No	Yes	712.2764	23341.95
No	Yes	1290.62	18408.05
No	Yes	1802.903	21411.42
No	Yes	770.0157	13684.79
No	Yes	401.3327	15332.02
No	Yes	999.2811	20013.35
No	Yes	172.413	14955.94
No	Yes	200.9222	16862.95