Econometrics: Simple Linear Regression (Mistakes to Avoid)
Requirements
- Basic knowledge of Simple Linear Regression so that you could understand the mistakes mentioned
Description
The purpose of this econometrics course is to share with you the confusion points and some of the silly mistakes that students do while studying Simple Linear Regression.
Mistake 1: Placement of error term in population & sample regression equations. Also, have you ever seen 'X hat' in any of the regression equations?
Mistake 2: What is it that we minimise in the method of OLS?
Do you first sum the sample errors and then square the sum?
OR
Do you first square the sample errors and then take the sum?
Mistake 3: Not practicing the mathematical expressions. There are multiple ways of writing the formula for 'B2 hat'. Do you know all of them?
Mistake 4: You must have encountered some assumptions while studying Simple Linear Regression. Do you put the assumptions on the sample error? Also, what is the mathematical expression for the sample error?
Mistake 5: Not paying enough attention to the assumptions and linkages.
Example: What do you think about the following two statements? True or False.
Statement 1: In the presence of heteroscedasticity, the OLS estimators are biased.
Statement 2: For OLS estimators to be BLUE, the population error should follow a normal distribution.
Mistake 6: Standard Deviation OR Standard Errors?
Mistake 7: Testing the hypothesis on estimators or parameters?
So, what are you waiting for? Get started with the course so that you don’t make the same mistakes in your final exam!
Who this course is for:
- University students who are new to Econometrics and want to avoid silly mistakes in their final exam
Instructor
- 4.5 Instructor Rating
- 773 Reviews
- 14,560 Students
- 9 Courses
Author of four e-books on Amazon (two for Statistics and two for Econometrics). I have 3500+ hours of teaching experience in the field of Microeconomics, Statistics and Econometrics. I became an online tutor in 2015 and have been teaching full time since then. I have worked with students who were complete beginners, as well as those who were facing challenges in mastering advanced topics.
I completely understand the initial struggle in decoding the concepts and formulas. I am adept in breaking down difficult concepts with the use of simple examples. I don't encourage memorisation and simply recalling the formulas, instead, I focus on the 'why' and 'how'.
I understand that every student has a different way of understanding things. Some students understand the concepts when explained through analogies, others when shown mathematical foundation behind them. I modify my teaching methodology depending on what the student is comfortable with.
I have worked with students from 90+ universities. Here are some of the courses I have catered to:
6012B0453Y : Econometrics (Amsterdam School of Economics)
EC226: Econometrics (University of Warwick)
EC203: Applied Econometrics (University of Warwick)
MG205: Econometrics - Theory and Applications (LSE)
EC3301: Statistics and Econometrics (University of St Andrews)
ECON W3412: Introduction to Econometrics (Columbia University)
BEE2031: Econometrics (University of Exeter)
Econometrics: University of Birmingham
BEE2006: Statistics and Econometrics (University of Exeter)
EC3303 : Statistics and Econometrics (University of St. Andrews)
EC304: Empirical Economic Analysis II (Boston University)
FR2202: Financial Econometrics (Cass Business School)
EC220: Introduction to Econometrics (LSE)
EC221: Introduction to Econometrics (LSE)
5SSMN932: Introduction to Econometrics (King’s College London)
5QQMN938 : Intermediate Econometrics (King’s College London)
5SSPP213: Econometrics (King’s College London)
BEE1023 : Introduction to Econometrics (University of Exeter)
6012B0212: Econometrics (Amsterdam School of Economics)