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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. 7,000**

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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**

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**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 Lectures****Demo PDF of Study Material**

Chapter-4-Probability

**Demo PDF of Study Material****Demo Quiz**

**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**

**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**

**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**

**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 **

**Solutions of Previous Year Papers**

**2021 Paper**

**Duration of Lectures : 110 Minutes**

**2020 Paper**

**Duration of Lectures : 100 Minutes**

**2019 Paper**

**Duration of Lectures : 120 Minutes**

**2018 Paper**

**Duration of Lectures : 110 Minutes**

**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

Core Course (CC) Credit: 6

**Course ObjectiveThe 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 OutcomesAt 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 importantlearning 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 1Introduction and overview The distinction between populations and samples and between population parameters and sample statistics**

**Unit 2Elementary probability theory Sample spaces and events; probability axioms and properties; counting techniques; conditional probability and Bayes’ rule; independence**

**Unit 3Random 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 4Random 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 5Point and interval estimation Estimation of population parameters using methods of moments and maximum likelihood procedures; properties of estimators; confidence intervals for population parameters**

**Unit 6Hypothesis 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.**