Intermediate Statistics for Economics

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Intermediate Statistics for Economics for Economics (H) Semester II, University of Delhi

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The Intermediate Statistics for Economics Course for BA (Hons) Economics Semester II, 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

Access of Video Lectures is provided on any one of the following devices:

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till end of Semester II 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 Exhaustively + Complete Solutions of Back Questions of readings + Solutions of Previous Years Papers + Large Number of Numericals

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Click Here for PDF Notes of Chapter 1

Note for Full Course PDF Notes you need to subscribe our course

Demo Lectures

Course Introduction
Central Limit Theorem
Confidence Interval Lecture #1

Course Content of Our Video Lectures

Lectures are as per Latest Syllabus for 2024 UGCF

Unit 1 : Sampling Distribution of a Statistic

Chapter 1 : Sampling

Duration of Lectures : 443 Minutes

Based Upon J L Devore Chapter 5 (Section 5.3, 5.4 & 5.5)

Topics Covered

►Sampling

►Statistics & Their Distributions, Statistic & Parameter

►The Distribution of the Sample Mean, Sampling Distributions

►Central Limit Theorem

►The Distribution of a Linear Combination

►Questions from Recent Eco (H) Examinations

►Back Questions of Readings

Unit 2 : Estimation

Chapter 2 : Point Estimation

Duration of Lectures : 307 Minutes

Based Upon J L Devore Chapter 6;

Topics Covered

►Point Estimate

►Minimum Variance Unbiased Estimator

►Standard Error of Estimator

►Maximum Likelihood Estimator

►Method of Moments

►Properties of Estimators

►Questions from Recent Eco (H) Examinations

►Back Questions of Readings

Chapter 3 : Confidence Interval

Duration of Lectures : 230 Minutes

Based Upon J L Devore Chapter 7;

Topics Covered

►Properties of a Confidence Interval

►Confidence Interval of a Single Mean for Large & Small Samples

►Confidence Interval of Proportion

►Confidence Interval of Variance

►Chi-Square and F Distribution

►Questions from Recent Eco (H) Examinations

►Back Questions of Readings

Unit 3 : Inference

Chapter 4 : Inference

Duration of Lectures : 120 Minutes

Based Upon J L Devore Chapter 8.1;

Topics Covered

►Meaning of Statistical Hypothesis

►Errors in Hypothesis Testing

►Type 1 & Type 2 Errors

►Power of a Test

►Questions from Recent Eco (H) Examinations

►Back Questions of Readings

Unit 4 : Hypothesis Testing

Chapter 5 : Hypothesis Testing

Duration of Lectures : 240 Minutes

Based Upon J L Devore Chapter 8.2 – 8.5;

Topics Covered

►Testing of a Population Mean for Large Samples

►Testing of a Population Mean for Small Samples

►Testing of a Population Proportion for Large Samples

►Testing of a Population Proportion for Small Samples

►Hypothesis Testing for Variance

►Questions from Recent Eco (H) Examinations

►Back Questions of Readings

Chapter 6 : Two Sample Tests

Duration of Lectures : 270 Minutes

Based Upon J L Devore Chapter 9

Topics Covered

►Testing Equality of Means for Two Large Samples

►Testing of Equality of Means for Two Small Samples

►Testing for Ratio of Variances

►Questions from Recent Eco (H) Examinations

►Back Questions of Readings

Click Here for Reading List

Mock Test (MCQ)

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Created by Dheerajadmin

Sampling Test #1

1. Please Read the Questions and all the options Carefully, Before Selecting Your Choice.
2. You are not Allowed to edit your answers after submission.
3. The Paper has ten Questions
4. Time Allowed is 10 Minutes.
5. It is necessary to enter your valid Email id to attempt this test.

 

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1 / 10

Any statistical measure which is computed from population data is known as

2 / 10

Which of the following is not a method of Random Sampling

3 / 10

A process of generalizing the results and findings from the sample survey and makes them applicable to every field of enquiry

4 / 10

The part of population which is examined with a view to estimate the characteristics of that population is called

5 / 10

In statistical language, the study of the aggregate of the objects is called

6 / 10

Suppose the population consists of only three individuals and the values of the variable x are as follows : x1 = 6, x2 = 9, x3 = 12.

All possible samples of size 2 are listed and mean of all such samples is computed. what is the mean of such means

7 / 10

A population consists of the numbers 12, 14 and 16. How many samples (with replacement) of size two which can be drawn from the population ?

8 / 10

A population consists of the numbers 12, 14 and 16. How many samples (without Replacement) of size two which can be drawn from the population ?

9 / 10

Consider the following Statements :

I : The probability distribution of a sample statistic is often called the sampling distribution of the statistic

II : Every statistic has a sampling distribution

10 / 10

Any statistical measure which is computed from sample data is known as

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Exam Pattern

The Question Paper will be of 90 Marks

Suggested weightage for each unit in the final examination

Unit I : 20 marks

Unit II : 30 marks

Unit III + Unit IV : 40 marks

Paper Pattern

All questions in Units 1 and 2 would be compulsory. There would be two questions in each of these units.

►Units 3 and 4 would together have 3 questions, of which students would be
required to do 2 questions.

►There would be a limited number of sub-parts per question. No sub-part would be less than 5 marks and if a sub-part had more than 5 marks, the marks would be in multiples of 5.

Readings Suggested by DU

Essential Reading :

Devore, J. (2012). Probability and statistics for engineers, 8th ed. Cengage Learning.

Supplementary Reading :

Hogg, R., Tanis, E., Zimmerman, D. (2021) Probability and Statistical inference, 10TH Edition, Pearson

Larsen, R., Marx, M. (2011). An introduction to mathematical statistics and its applications. Prentice Hall.

Miller, I., Miller, M. (2017). J. Freund’s mathematical statistics with applications, 8th ed. Pearson.

Anderson, D. R, Sweeny, D. J, et. al (2019), Statistics for Business and Economics, 13th edition, Cengage Learning.

Jan Kmenta (1997), Elements of Econometrics, 2nd ed. Macmillan publishing; New York and Collier Macmillan; London.