Predictive Analytics and Modeling using Minitab

This course contains the following basic steps involved in predictive modeling

• Defining the objective – This section deals with the ways to define the objective of predictive models with relation to the goals of the business.
• Gathering the data -Collecting data from various sources is another important step in building predictive model. Examples are provided for collection of different types of data from various sources.
• Preparing the data for modelling – This section deals with the segregation of data and how determines how they can be used in predictive modeling.
• Selecting and transforming the variables – This topic deals with the steps for transformation of independent variables to best fit the dependent variable.
• Processing and evaluating the model – In this chapter you will go through several methods of processing and evaluating the model
• Validating the model – The predictive models should perform well on the data. This chapter deals with three powerful methods for ensuring the model fit.
• Implementing and maintaining the model – Effective implementation of Predictive model is another important step. This chapter discusses various auditing procedures and model maintenance practices

Predictive analytics is an emerging strategy across many business sectors and they are used to improve the performance of the companies. Predictive modeling is a part of predictive analytics which is used to create a statistical model to predict the future behaviour. The predictive modeling can be used on any type of event regardless of its occurrence. The predictive model to be used for a particular situation is often selected on the basis of the detection theory. This course includes an overview of predictive analytics and predictive modeling. This course also includes examples of predictive modeling.