What is the best Regression Analysis Method to use?Category: General Posted:Oct 27, 2014 By: admin
Regression Analysis is the best method to analyse the relationships between the variables. It is used for multiple purposes like finding the causal effect, predicting and forecasting the effect of one variable on the other. Like increase in salary can lead to increase of spending capacity of an employee. It is an important tool to analyse and model data.
The relationship is analysed between independent and dependent variables. There are different types of regression testing like linear regression, least squares method and nonlinear regression. So when we have so many regression techniques which are the best one to use? Depending on the characteristic of data we choose the regression technique. The first step is to identify the relationships of different variables, their effects and importance. Then understand the coefficient of determination, standard errors and parameters. This can lead to precision in the results. As we know if the model is simple it shall produce accurate results. If a problem is complex, it is not necessary to use complex model to find solution for the problem. The complex problem is broken into simplex parts to find a solution for the problem. While working on causal relationships, one must tread carefully. Causation is not always a result of correlation. In short to regression analysis requires proper interpretation of data and sound analytics or reasoning. Regression analysis is an effective tool used in Lean Six Sigma.
At ZaranTech, role based training is provided for Lean Six Sigma (Green Belt). The course curriculum includes assignments, live sessions, quizzes, case studies, practical demo session. Hence the student gets acquainted with the tool and its application. We also provide Lean Six Sigma Certification material to clear the certification. To view the details of the course you may visit the website http://www.zarantech.com/course-list/sixsigma. Call 515-978-7846 or email [email protected]