To improve our practice with the multiple logistic regression, we look at another example. This time, we will use the UCBAdmissions dataset that contains aggregate data on applicants to graduate school at Berkeley for the six largest departments in 1973, classified by admission and sex. As such, this is a multiple logistic regression modeling problem. Input attributes include things like sex, departments, and admission attributes. A brief database description is given in the following list:
- Name: UCBAdmissions
- Package: datasets
- Number of instances: 4526
- Number of attributes: 3 categorical attributes
Each of the attributes is detailed in the following table:
| No | Name | Levels |
| 1 | Admit |
