« Back How to Choose the Right Type of Regression Sas Training Techniques

By vikas  |  SAS Programming  |  On 6/18/2018 10:01:09 PM

One of the most important topics in any course SAS Training In Pune is the use of regression and its practical application in various business scenarios. We have identified 7 key types of regression techniques that present a range of different use cases for different types of problem solving and various types of variables used in relation to each other.

 As a skilled student of  SAS Training In Pune  you would know these 7 techniques as below:

  1. Linear Regression
  2. Polynomial Regression
  3. Logistic Regression
  4. Ridge Regression
  5. Lasso Regression
  6. Stepwise Regression
  7. ElasticNet Regression


Now the question arises for a student of SAS Classroom Training In Pune – how to determine which regression techniques to use for which type of business problems. If you are wondering about the same problem then you are at the right place as you will be likely to find an answer here.


It is important to choose the best type of regression technique based on the type and number of dependent and independent variables. Other important characteristics of making this selection include the dimensionality of data among other key characteristics of the dataset being analyzed by experts of SAS training Pune.


Here are a few factors worth considering when working with different options in regression techniques:

1 – It is important to spend time on data exploration. This step should come before creating the predictive models. Working on data exploration is needed to ascertain the inter-relationship among variables and their impact on each other. 


2 – Know about the different types of influencers or success drivers that can impact your regression analysis. Professionals in SAS Course Training in Pune can pick from R-square, AIC, BIC, or error term. Another way is to eliminate bias by comparing the model with other sub-models.


3 – Interested to know of a good step to assess the models used for prediction? Then try out cross validation. You can separate the dataset into multiple groups like ‘train’ and ‘validate’. Then employ mean squared difference to the groups. For students of SAS training Pune, this will give you a precise measure of the prediction’s accuracy



In this post, it is made clear for students of SAS training Pune about which regression technique to apply for which type of business problem. With this knowledge, you can add substantial value to your responsibilities and carry out an expert job.