Econometrics Q

Tags: Econometrics

Regression Analysis and Statistical Modeling

Last updated 2022-01-10 | 4.2

- Simple Linear Regression
- Multiple Linear Regression
- Durbin-Watson Test Statistic

What you'll learn

Simple Linear Regression

Multiple Linear Regression

Durbin-Watson Test Statistic

Multivariate Regression

Polynomial Regression

Logistic Regression

Autoregressive Model

Vector Autoregressive Model

* Requirements

* Basic knowledge of statistics

Description

This course is essentially designed for economics students. Econometrics is a mandatory course to be completed in every Economics curriculum at university. The core classes an economics student has to complete in order to graduate are Microeconomics, Macroeconomics, Mathematical Economics, and Econometrics. And Econometrics is known to be the most difficult of all.

Econometrics has the reputation of being a fearful discipline and many students have been intimidated by the subject. Econometrics is used everywhere and in almost every professional industry on a daily basis to make decisions. Businesses use it to decide how to promote a product and their brand, schools use it to determine their admission rate, the government uses it to predict voting patterns and outcomes, hospitals use it to predict the spread of diseases, Banks and hedge funds use it to determine the price of the stock market and the trend of financial markets...etc. Econometrics is part of our lives.

The primary goal of this course is to demystify the field of Econometrics. It is meant to facilitate the understanding of complex econometric subjects. This course is structured to provide the foundational knowledge required to do econometric analysis and statistical modeling. It teaches the basic and advanced methods of econometric modeling.

Who this course is for:

beginners in data science
students of economics
beginners in statistics
students of mathematics

Course content

2 sections • 12 lectures

Basic Methods 7 lectures

Introduction to Econometrics Preview 11:19

In this video, you will learn the definition and purpose of econometrics. This video will review the following methods we will be learning throughout the course.

Simple Linear Regression: Basic Concepts Preview 12:38

This tutorial will teach you a basic understanding of the simple linear regression. It will address the various statistical properties (assumptions) that the model must fill in order to be valid.

Simple Linear Regression: Estimation of Parameters Preview 09:24

This tutorial will teach how the parameters of a simple linear regression are calculated.

Simple Linear Regression: Outliers Preview 08:14

This tutorial will teach you what an outlier is and how it could impact the outcome of a simple regression.

Multiple Linear Regression: Basic Concepts Preview 11:48

In this tutorial, you will learn the basic foundations of the multiple linear regression. Like the tutorial on the simple linear regression, this tutorial will address the various statistical properties as well required for the model to be valid.

Multiple Linear Regression: Estimation of Parameters Preview 11:07

This tutorial will teach you how to determine and calculate the various parameters of the multiple linear regression.

Autocorrelation: Durbin-Watson Test Statistic Preview 16:54

This tutorial will teach you what is an autocorrelation, and how to determine it by using the Durbin-Watson test statistic.

Advanced Methods 5 lectures

Multivariate Regression Preview 24:01

This tutorial will teach you the foundational approach to the multivariate regression. It will teach you how the model is designed and used.

Logistic Regression Preview 16:25

This tutorial will teach you the foundational methods and approach to the logistic regression. You will learn how to model categorical data.

Polynomial Regression Preview 12:17

This tutorial will teach you the foundational methods of the polynomial regression. It will essentially teach you the circumstances in which the polynomial regression is explicitly applied.

Autoregressive Model Preview 10:41

This tutorial will teach you the basic methods of the autoregressive model and how it is applied to time-series data.

Vector Autoregressive Model Preview 16:27

This tutorial will teach you the methods of the vector autoregressive model, which is an extension of the autoregressive model and a multivariate form of regression analysis for time-series.