Introduction To Econometrics 2022

Basics of Econometrics

What you'll learn
Nature & Scope of Econometrics
Introduction to Statistics - Univariate & Bivariate Distributions
Classical Linear Regression Model, Multiple Linear Regression Model & Probability Distributions
Violations of CLRM - Heteroscedasticity, Multicollinearity & Autocorrelation, Specification Analysis
Requirements
High School Economics
Description
A comprehensive study on 'Introductory Econometrics' is designed keeping in mind the Principles of Econometrics as part of syllabus covered for high school undergraduates at central universities in different parts of the world. At 'The Saviour Academy', we welcome you all to learn such a platform wherein we'll be focusing upon the most important concepts from the examination perspective used under 'Introductory Econometrics' such as "Review of Statistics", "Classical Linear Regression Model (CLRM)", "Multiple l Linear Regression Model (MLRM)", "Heteroscadasticity","Autocorrelation" as well as "Multicollinearity" like its "Causes & Consequences", "Durbin-Watson Test", "White's Test", "OLS Methods of Least Squares" and "Specification Analyses" with the help of technical tools, educational software and indeed with a lot of self-explanatory diagrams in a three-dimensional platform and then we say it had revolutionized the method of smart classes very well.Econometrics is the application of statistical methods to economic data in order to give empirical content to economic relationships. More precisely, it is "the quantitative analysis of actual economic phenomena based on the concurrent development of theory and observation, related by appropriate methods of inference". A basic tool for econometrics is the multiple linear regression model. Econometric theory uses statistical theory and mathematical statistics to evaluate and develop econometric methods. Econometricians try to find estimators that have desirable statistical properties including unbiasedness, efficiency, and consistency.

Overview

Section 1: Introduction

Lecture 1 AN INTRODUCTION TO ECONOMETRICS

Section 2: Review of Statistics

Lecture 2 DESCRIPTIVE STATISTICS, RANDOM VARIABLES & PROBABILTY DENSITY FUNCTIONS

Section 3: Classical Linear Regression Model

Lecture 3 3. CLASSICAL LINEAR REGRESSION MODEL - AN INTRODUCTION

Section 4: Multiple Regression

Lecture 4 MULTIPLE REGRESSION - AN INTRODUCTION

Section 5: Violations of Classical Assumptions

Lecture 5 5.VIOLATIONS OF CLASSICAL ASSUMPTIONS

Section 6: Dummy Variables & Specification Analysis

Lecture 6 6.DUMMY VARIABLES

BA (HONS) ECONOMICS, BCOM(HONS), BBE, BA, BCOM - Introductory Microeconomics.

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