Statistical Methods

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The Statistical Methods for Economics 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 : Rs. 6000

Access of Video Lectures is provided on one device, Windows Computer or Android Phone, till end of Semester III Exams.

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  • Full Course Video Lectures
  • Complete Study Material (PDF Notes) which includes Concepts, Previous Year Questions, Numerical Questions, MCQ’s and Important Questions
  • Online Discussion Forum to Post Your Queries to Discuss with Faculty & other fellow Students
  • Live online Doubts Sessions (at least twice a week) for resolution of Doubts
  • Mock Tests at the Website
  • Video Lectures Cover Theory Portions Exchaustively + Complete Solutions of Back Questions of readings + Solutions of Previous Years Papers + Large Number of Numericals

On Payment of Fee we will create your account on our website & you need to login and download all the lectures & our APP through that login account

Access of Video Lectures is provided on one device, Windows Computer or Android Phone, till end of the Semester II Exams

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Demo Lectures

Demo PDF of Study Material

Chapter-4-Probability

Demo Quiz

Probability Demo Quiz #1

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3. The Paper has ten Questions
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Exam Pattern

Assessment :

This course carries 100 marks of which the end semester examination is 75 marks and internal assessment is worth 25 marks as per the following norms: Two class tests/assignment of 10 marks each and 5 marks for attendance.

The following distribution of topics and marks, and the amount of choice within each topic, was agreed upon:
a. Section 1: Unit 1 and Unit 2: (indicative weightage 10 marks), Two questions of 5 marks each with one question from Unit 1 and the other from Unit 2. No internal choice in these units should be given.
b. Section 2: Unit 3 and Unit 4: (indicative weightage 25 marks), One compulsory question of 5 marks and Two questions out of Three for 10 marks each.
c. Section 3: Unit 5: (indicative weightage 20 marks), Two questions out of Three for 10 marks each.
d. Section 4: Unit 6: (indicative weightage 20 marks), Two questions out of Three for 10 marks each.

Course Content of Our Video Lectures

Unit – I : Introduction & Overview

Chapter 1 : Introduction & Overview [60 Minutes]

Based Upon J L Devore Chapter 1.1

Number of Lectures   1 Lectures

Total Duration   60 Minutes

Number of Questions in Notes   10 Questions

Number of MCQ Tests on this Chapter   1 Tests

Important Topics Covered : Population & Sample

Unit – II : Elementary Probability Theory

Chapter 2 : Probability [542 Minutes]

Based Upon J L Devore Chapter 2

Number of Lectures   13 Lectures

Total Duration   542 Minutes

Number of Questions in Notes   376 Questions

Number of MCQ Tests on this Chapter   6 Tests

Important Topics Covered : Sample space, Events, Use of Combinations & Permutations, Addition Theorem, Conditional Probability, Independent Events & Multiplication Theorem, Bayes Theorem, Mathematical Expectation

Unit – III : Random Variables & Probability Distributions

Chapter 3 : Discrete Random Variables [521 Minutes]

Based Upon J L Devore Chapter 3

Number of Lectures   11 Lectures

Total Duration   521 Minutes

Number of Questions in Notes   229 Questions

Number of MCQ Tests on this Chapter   6 Tests

Important Topics Covered : Discrete Random Variable, PMF, CDF, Binomial Distribution, Hypergeometric Distribution, Poisson Distribution

Chapter 4 : Continuous Random Variables [337 Minutes]

Based Upon J L Devore Chapter 4

Number of Lectures   8 Lectures

Total Duration   337 Minutes

Number of Questions in Notes   102 Questions

Number of MCQ Tests on this Chapter   6 Tests

Important Topics Covered : Probability Density Function, CDF, Uniform Distribution, Normal Distribution, Exponential & Gamma Distribution

Unit – IV : Random Sampling & Jointly Distributed Random Variables

Chapter 5 : Joint Probability DIstributions [243 Minutes]

Based Upon J L Devore Chapter 5

Number of Lectures   5 Lectures

Total Duration   243 Minutes

Number of Questions in Notes   60 Questions

Number of MCQ Tests on this Chapter   4 Tests

Important Topics Covered : Joint PMF, Marginal PMF, Joint PDF, Marginal PDF, Conditional Distributions, Covariance, Correlation, Properties of Correlation, Statistics & their Distribution, Distribution of Sample Mean, Distribution of a Linear Combination

Unit – V : Point & Interval Estimation

Chapter 6 : Point Estimation [307 Minutes]

Based Upon J L Devore Chapter 6

Number of Lectures   7 Lectures

Total Duration   307 Minutes

Number of Questions in Notes   68 Questions

Number of MCQ Tests on this Chapter   5 Tests

Important Topics Covered : Sampling, Point Estimate, MVUE, Standard Error of an Estimator, MLE, Method of Moments, Central Limit Theorem

Chapter 7 : Confidence Intervals [230 Minutes]

Based Upon J L Devore Chapter 7

Number of Lectures   5 Lectures

Total Duration   230 Minutes

Number of Questions in Notes   73 Questions

Number of MCQ Tests on this Chapter   5 Tests

Important Topics Covered : Properties of a Confidence Interval, Confidence Interval of a Single Mean & Proportion, t & chi square distribution, Confidence Bounds

Unit – VI : Hypothesis Testing

Chapter 8 : Hypothesis Testing [212 Minutes]

Based Upon J L Devore Chapter 8

Number of Lectures   4 Lectures

Total Duration   212 Minutes

Number of Questions in Notes   66 Questions

Number of MCQ Tests on this Chapter   4 Tests

Important Topics Covered : Hypothesis Testing, Type I & Type II Errors, Power of a Test, P Values

Previous Year Papers

SME 2018

SME 2019

End of Syllabus

Syllabus for SME as Prescribed by University of Delhi

Minutes-of-Meeting

Course Description

Statistical Methods for Economics (HC33)
Core Course (CC) Credit: 6

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

References

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.