Regression Analysis with EViews

Web Base Course

10.00 – 16.00 (GMT) May 26, 2010

10.00 – 16.00 (GMT) July 21, 2010


Course description
About EViews

Level: Introductory

Course Overview

The classical linear regression model or regression analysis is the most commonly used technique in the field of applied econometrics. This course covers both the theory and practice of regression analysis, however, the emphasis is on practical aspects through real life applications and exercises. The course focus on several issues and challenges frequently encountered when building econometric models. Upon completion of the course, you will have gained valuable skills that will help you build statistically sound models and make efficient use of EViews capabilities.

Topics Include:

  • Linear vs. non-linear models
  • Diagnostic testing (heteroskedasticity, autocorrelation, parameter stability, etc)
  • The problem of spurious regression
  • Dealing with violations of the classical linear regression model assumptions
  • Other topics in regression analysis: multicollinearity, dummy variables, outliers/influential observations


Who should attend ? 

If you can associate with one or more of the following statements, then this course is for you.

  • I have enough data but I do not know where to start from.
  • My models do not give the results that I expect. Am I missing something?
  • I want to build more advanced models and capture complex relationships.
  • My model fails one or more diagnostics. What shall I do? Are my results still valid?
  • I have built a number of competing models but I do not know which one to choose.
  • I do not have much faith in econometrics as in the past it failed to give me the answer I expected.

Prerequisites: Knowledge of EViews Basics. Previous experience on data analysis is advantageous.

Cost - The cost of the course is:

Commercial
£350+VAT
Academic £250+VAT
Students £50 + VAT

To register or request more information,
please contact us.
email: training@timberlake.co.uk;
telephone: 0044 20 8697 3377

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