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Quick Facts

Medium Of Instructions	Mode Of Learning	Mode Of Delivery
English	Self Study	Video and Text Based

Course Overview

The objective of econometrics is to measure economic relations. Therefore, the Introduction to Econometrics certification course by Swayam aims to use financial data, mathematical models, and statistical tools to bring empirical evidence to various economic theories. The course is equipped with theory concepts as well as practical training, allowing candidates to apply and practice problems and solutions.

The Introduction to Econometrics certification syllabus covers numerous technical concepts like classic linear regression model, multiple linear regression model, application of F statistics, dummy variable models, qualitative response models, and the like. The course deals not only in economics but also in social science and pure science.

Besides, the Introduction to Econometrics online course is taught by eminent Prof. Sabuj Kumar Mandal from the prestigious IIT Madras. This 12-week, AICTE approved course helps students get a broad overview of econometrics, data analysis, humanities, and social sciences and prepares them to explore the field further.

The Highlights

Undergraduate level
AICTE approved, FDP course
E-certificate on completion
Elective course
Final assessment
Weekly assignments
12-week course
Free course
100% online course

Programme Offerings

Final Assessment
Undergraduate level
100% online course
AICTE approved
FDP course
free course
E-certificate on completion
12-week study
elective course
Weekly Assignments

Courses and Certificate Fees

Fees Informations	Certificate Availability	Certificate Providing Authority
INR 1000	yes	IIT Madras

The Introduction to Econometrics online course is a free course but to avail a certificate, candidates must pay a fee of Rs 1,000.

The Introduction to Econometrics fee structure

Course option	Fee
Introduction to Econometrics (Audit only)	Free
Introduction to Econometrics (With certificate)	Rs 1,000

Eligibility Criteria

Anyone who wants to join the Introduction to Econometrics online program should know inferential statistics as it’s a prerequisite to the course.

Certificate Qualifying Details

All candidates must attempt all the weekly assignments and the final examination to be eligible for the certificate.

What you will learn

Knowledge of Econometrics

Once candidates finish the Introduction to Econometrics Certification syllabus, they will learn the following:

All about econometric analysis
Understanding regression analysis
How to perform hypothesis testing
How to apply F statistics
All about the linear regression model
Understanding dummy variable models
All about Heteroskedasticity
Understanding quantitative response models

Who it is for

The Introduction to Econometrics certification course is for anyone interested in data analytics or who wants to pursue a career in econometrics such as students, professionals, or researchers.

Admission Details

The Introduction to Econometrics Certification program by Swayam requires candidates to register on the platform as given below:

Visit Swayam’s official website: https://swayam.gov.in/
On the search bar, type the course name, “Introduction to Econometrics” and click on it below.
On the course page, click on the “Join” button to the top left, to get directed to the account creation page.
Here, to create an account, candidates need to login on to the platform with their existing email IDs or create a new one.
A verification mail will be sent upon successful registration. Once verification is done, candidates can start to learn the course.

Application Details

Interested learners of Introduction to Econometrics training must register for the course on the Swayam platform by creating a new account by giving their name, email id, and password. Alternatively, they can sign up using their existing Google, Microsoft, or Facebook IDs. Candidates do not need to fill any application form.

The Syllabus

Introduction to Econometrics
Econometric Analysis
Steps involved in Econometric Analysis

Introduction to the classical linear regression model
The two-variable classical linear regression model
Assumptions of Classical Linear Regression Model

Classical linear regression model assumptions
Properties of ordinary least square estimators
Estimation of the regression model

Regression analysis: Objective
Statistical Analysis
Interpretation of results
Hypothesis testing-Types of Hypothesis
Test statistic
Critical Region

Hypothesis testing: Level of significance and confidence interval approach
Goodness of Fit(R^2): Concepts of Explained Sum of Squares (ESS)
Residual Sum of Squares
Total Sum of Squares

Multiple Linear Regression Model: Interpretation of the model
Statistical Analysis
Interpretation of the results

Model misspecification: R^2 vs Adjusted R^2
F statistics
Application of F statistics
Overall significance of the model
Equality between two regression coefficients
Testing the validity of linear restricted and Unrestricted models

Application of F statistics: Testing structural break in Time Series data
Chow test
Limitations of chow test
Dummy Variable models: Introduction
Different types- ANOVA, ANCOVA

Dummy variable models continued
Application of Difference-In-Difference for impact evaluation
Statistical Analysis of the Dummy variable models

Dummy variable model for testing seasonal fluctuation: Introduction, Analysis, Dummy variable trap
Relaxing the assumptions of Classical Linear Regression Model: Multicollinearity-Introduction-Consequences-Detection-Remedial measures
Autocorrelation-Introduction-Consequences-Detection-Remedial measures

Heteroskedasticity: Introduction- Consequences-Detection-Remedial measures
Qualitative Response Models: Linear Probability Model, Logit Model

Qualitative Response Models: Probit model
Alternative measures of Goodness of Fit (R^2) in Qualitative response models
Logit vs Probit model selection
Limited dependent variable model/ Tobit Model

Evaluation process

The precondition to the certificate eligibility is candidates must score a passing percentage of 40% in the weekly assessments and an average of 40% in the final evaluation. Students won’t receive a certificate if they fail to meet these criteria.