Statistical Methods for Economics

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The Statistical Methods for Economics - I Course for BA (Hons) Economics Semester III, Delhi University has been taught by Mr. Dheeraj Suri. The Video Lectures are based upon the books prescribed by the University of Delhi. The Duration of Video Lectures is approximately 50 Hours.
Course fee is Rs. 6000
Access of Video Lectures is provided on one device, Windows Computer or Android Phone, till end of Semester III Exams.
Once You get the access you need to login and download our APP and all the lectures from your login account and play in your device.


You will Get

  • Full Course Video Lectures
  • Complete Study Material, which covers Important Questions and Questions from Previous Year Exams (Total of 1300 Questions)
  • Video Lectures Cover Theory Portions Exchaustively + Complete Solutions of Back Questions of readings + Solutions of Previous Years Papers + Large Number of Numericals
  • Live Online Doubts Sessions.


For Demo Lectures Click on the Following Links


Course Content
Unit 1 : Introduction and Overview
Note : Chapter 1, Chapter 2 & Chapter 3 have been deleted from the latest syllabus, but we have kept them for the sake of basics
Chapter 1 : Descriptive Stats  [95 Minutes]




Chapter 2 : Measures of Central Tendency  [272 Minutes]

Arithmetic Mean


Trimmed Mean


Quartiles, Deciles and Percentiles


Chapter 3 : Measures of Dispersion  [203 Minutes]

Range & Coefficient of Range

Quartile Deviation and its Coefficient

Mean Deviation and its Coefficient

Standard Deviation and Variance

Sample Standard Deviation

Fourth Spread


Semester 3 Syllabus Starts from Here

Unit 2 : Elementary Probablity Theory
Chapter 4 : Probability Theory   [542 Minutes]

Probability of An Event

Use of Combinations in Probability

Use of Permutations in Probability

Addition Theorem of Probability

Conditional Probability

Multiplication Theorem of Probability

Law of Total Probability

Bay’s Theorem

Mathematical Expectation


Unit 3 : Random Variables and Probability Distributions
Chapter 5 : Discrete Random Variables  [272 Minutes]

Probability Distribution of Discrete Random Variable

Binomial Distribution

Poisson Distribution


Chapter 6 : Continuous Random Variables  [337 Minutes]

Probability Distribution of continuous Random Variable

Uniform Distribution

Normal Distribution

Exponential Distribution


Unit 4 : Random Sampling and Jointly Distributed Random Variables
Chapter 7 : Joint Distributions   [196 Minutes]

Joint Probability Mass Function

Joint Probability Density Function


Scatter Diagram Method

Karl Pearson’s Coefficient of Correlation

Properties of Correlation Coefficient

Corrected Correlation Coefficient

Proof’s on Correlation


Unit 5 : Point and Interval Estimation
Chapter 8 : Sampling  [290 Minutes]


Theory of Estimation

Methods of Point Estimation

Maximum Likelihood Estimation

Method of Moments

Standard Error of Statistic

Central Limit Theorem

Distribution of Linear Combination


Chapter 9 : Confidence Interval  [151 Minutes]

Confidence Limits for Single Mean

Confidence Limits for Single Proportion

Students’s ‘t’ Distribution

Chi-Square Distribution


Unit 6 : Hypothesis Testing
Chapter 10 : Hypothesis Testing  [283 Minutes]

Hypothesis Testing of Single Mean for Large Samples

Hypothesis Testing of Single Mean for Small Samples

Hypothesis Testing of Single Proportion

Hypothesis Testing of Variance

Type I and Type II Errors

Hypothesis Testing of Difference between Two Means


Previous Year Papers

2017 Paper

2018 Paper

2019 Paper


Course Description
Course Objective
The course teaches students the basics of probability theory and statistical inference. It sets a necessary foundation for the econometrics courses within the Honours programme. The familiarity with probability theory will also be valuable for courses in advanced microeconomic theory. 
Course Learning Outcomes 
At the end of the course, the student should understand the concept of random variables and be familiar with some commonly used discrete and continuous distributions of random variables. They will be able to estimate population parameters based on random samples and test hypotheses about these parameters. An important learning outcome of the course will be the capacity to analyse statistics in everyday life to distinguish systematic differences among populations from those that result from random sampling.  
Unit 1
Introduction and overview The distinction between populations and samples and between population parameters and sample statistics 
Unit 2
Elementary probability theory Sample spaces and events; probability axioms and properties; counting techniques; conditional probability and Bayes’ rule; independence  
Unit 3
Random variables and probability distributions Defining random variables; probability distributions; expected values and functions of random variables; properties of commonly used discrete and continuous distributions (uniform, binomial, exponential, Poisson, hypergeometric and Normal random variables) 
Unit 4
Random sampling and jointly distributed random variables Density and distribution functions for jointly distributed random variables; computing expected values of jointly distributed random variables; covariance and correlation coefficients  
Unit 5
Point and interval estimation Estimation of population parameters using methods of moments and maximum likelihood procedures; properties of estimators; confidence intervals for population parameters  
Unit 6
Hypothesis testing Defining statistical hypotheses; distributions of test statistics; testing hypotheses related to population parameters; Type I and Type II errors; power of a test; tests for comparing parameters from two samples 
1. Devore, J. (2012). Probability and statistics for engineers, 8th ed. Cengage Learning.
2. Larsen, R., Marx, M. (2011). An introduction to mathematical statistics and its applications. Prentice Hall.
3. Miller, I., Miller, M. (2017). J. Freund’s mathematical statistics with applications, 8th ed. Pearson.  
Video Lectures are also available for :
Eco (H) Sem I
Mathematical Methods for Economics I
Introductory Micro Economics
Calculus (GE)
Eco (H) Sem II
Mathematical Methods for Economics II
Introductory Macro Economics
Linear Algebra (GE)
Eco (H) Sem III
Intermediate Micro Economics I
Intermediate Macro Economics I
Statistical Methods
Financial Economics (SEC)
Data Analysis (SEC)
Differential Equations (GE)
Money and Banking (GE)
Eco (H) Sem (IV)
Intermediate Micro Economics II
Intermediate Macro Economics II
Introductory Econometrics
Data Analysis
Eco (H) Sem V
Development Economics I
Indian Economy I
Applied Econometrics
International Economics
Public Economics
Eco (H) Sem VI
Development Economics II
Financial Economics
Money & Financial Markets
Environmental Economics
BBE ALL Semester
B Com (H) ALL Semester
MA Economics Entrance
UGC NET Economics


For any query feel free to contact at
Dheeraj Suri Classes
Prime Academy