Portfolio Milestone – Bank Marketing
Introduction
Explore the dataset by providing summary statistics and graphical summaries of all the variables. Explain some of the key aspects of data in part 1.
Figure 1
Summary statistics for the ten numeric variables of the Bank dataset.Note. Created using SAS Studio. Copyright © 2012-2018, SAS Institute Inc., Cary, NC, USA.
Figure 2
Histogram for the ten numeric variables of the Bank dataset.
Note. Created using SAS Studio. Copyright © 2012-2018, SAS Institute Inc., Cary, NC, USA
Examine if the dataset has any anomalies. Describe the method(s) you used as well as the results.
Examine if there are any association among the variables. Describe the approaches as well as the results.
Using one of the clustering techniques, analyze all the quantitative variables. Explain the results.
As an example, I used K-means with variables age, campaign, and consumer confidence index
Using one of the classification techniques from the course, build the model that predicts whether the client will subscribe. Explain why you think the model you’ve chosen is most appropriate for this dataset.
For example, using the variables education, loan, age, and campaign to build a logistic regression scenatio.
