Session
Management, Business and Economics
Description
A model is a statement of reality or its approximation. Most phenomena in the social sciences are extremely complex. With a model we simplify the reality and focus on a manageable number of factors. It is impossible to completely understand why consumers default and identify all the factors influencing customer’s default behavior. The bank manager sets up a statistical model that relates customer’s default behavior to only two important factors, the income and the education. There surely are thousands of other variables that may influence customer’s default behavior. This article describes the fundamentals of a statistical model building. We begin our discussion on the managerial justification for building a statistical model. Then we discuss three important statistical issues that are of prime importance to database marketers: model/variable selection, treatment of missing data, and evaluation of the model using Bootstrap Method.
Keywords:
Predictive modelling, Customer, Evaluation, Bootstrap Method
Proceedings Editor
Edmond Hajrizi
ISBN
978-9951-550-12-3
First Page
93
Last Page
98
Location
Durres, Albania
Start Date
7-11-2015 9:00 AM
End Date
7-11-2015 5:00 PM
DOI
10.33107/ubt-ic.2015.28
Recommended Citation
Kushta, Elmira; Pajo, Miranda; and Gjermeni, Orgeta, "Statistical Issues in Predictive Modelling using Bootstrap Method" (2015). UBT International Conference. 28.
https://knowledgecenter.ubt-uni.net/conference/2015/all-events/28
Included in
Statistical Issues in Predictive Modelling using Bootstrap Method
Durres, Albania
A model is a statement of reality or its approximation. Most phenomena in the social sciences are extremely complex. With a model we simplify the reality and focus on a manageable number of factors. It is impossible to completely understand why consumers default and identify all the factors influencing customer’s default behavior. The bank manager sets up a statistical model that relates customer’s default behavior to only two important factors, the income and the education. There surely are thousands of other variables that may influence customer’s default behavior. This article describes the fundamentals of a statistical model building. We begin our discussion on the managerial justification for building a statistical model. Then we discuss three important statistical issues that are of prime importance to database marketers: model/variable selection, treatment of missing data, and evaluation of the model using Bootstrap Method.