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Instructors: Ahmad Robin Sedeqi
6 sections * 27 lectures * 1h 57m
Video: MP4 1280x720 44 KHz | English + Sub
Updated 5/2021 | Size: 739 MB
Learn all the concepts and practices to perform a regression analysis
What you'll learn
Econometrics definition and basics, Practical Regression Analysis with Eviews, Regression diagnosis with Eviews
Requirements
Basic knowledge of statistics is preferred but not necessary
Description
As we all know regression analysis is a very common analysis in researches and understanding how to do it, is very necessary for every college and university student. This is a complete conceptual and practical econometrics course on udemy. Students will understand basics of econometrics such as what each component means and how they contribute to a successful econometrics analysis. Moreover, students will get familiar with formulas of calculating OLS using excel and later how they can perform regressions more easily using Eviews (statistical software). Some of the common problems during regression analysis are explained and remedies were purposed.
After taking this course your will be able to perform regression analysis for your research projects and you will get familiar on how to use Eviews software for statistical analysis.
Course has divided in to 3 main sections as follow
1- Basics
Here you will learn all the basics of statistical analysis such as measurements of scale, type of variables and ...
2- OLS
In this section you will understand what OLS is and why it is the best linear estimator, theories are explained in a very easy and understandable manner. Other components such as R squared, error term and ... discussed
3- OLS diagnosis
Common problems which are arising during a regression analysis has been discussed and practically diagnosed using Eviews(statistical software).
A bonus lecture and some other benefits such as how to use Eviews you will get by using this course
For any questions you can post it in the Q/A section and we will try best to respond to it in 24 hr
Who this course is for
Anyone curios about data science, statistics, hypothesis testing and research writing
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