Introductory Statistics for Economics

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►Introductory Micro Economics

►Introductory Mathematical Methods for Economics

►Introductory Statistics for Economics

►GE Calculus

►GE Statistical Methods

The Introductory Statistics for Economics (ECON 003) Course for BA Economics (Honours) UGCF Semester I, 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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till end of Semester I 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 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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Exam Pattern

1. The following is distribution of topics, indicative weightage, and the amount of choice within each section

  • Section 1: Unit 1 and Unit 2: (weightage 20 marks), Two questions of 10 marks each with one question from Unit 1 and the other from Unit 2. Internal choice in these units should be given as 2 out of 3 questions
  • Section 2: Unit 3: (weightage 20 marks), Two questions out of Three for 10 marks each.
  • Section 3: Unit 4: weightage 20 marks), Two questions out of Three for 10 marks each.
  • Section 4: Unit 5: (weightage 15 marks), Three questions out of Four for 5 marks each.

2. There would be no compulsory question in any of the sections.

3. The internal assessment would comprise of 10 marks Class test, 10 marks Class test/assignment. Attendance will carry 05 marks.

4. the question paper will include internal choice in each section with limited number of sub-parts.

5. In order to achieve uniformity in evaluation of final answer scripts, it was decided to include the following note in final question paper:

  • All questions within each section are to be answered in a contiguous manner on the answer sheet. Start each question on a new page, and all sub-parts of a question should follow one after the other.
  • All intermediate calculations should be rounded off to 3 decimal places. The values provided in statistical tables should not be rounded off. All final calculations should be rounded off to two decimal places.

Click Here for Reading List of Introductory Statistics for Economics

Click Here for Demo PDF of Study Material

Demo Lectures

Introductory Stats Class #1
Introductory Stats Class #2
Probability Lecture #1
Probability Lecture #2
Probability Lecture #3
Probability Lecture #4

Demo Mock Tests

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Time Allowed for this Test is 20 Minutes

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Created by Dheerajadmin

Probability 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 twenty Questions
4. Time Allowed is 20 Minutes.
5. It is necessary to enter your valid Email id to attempt this test.

 

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1 / 20

What is the probability of 53 Sundays in a leap year

2 / 20

Tickets numbered 1 to 200 are mixed and a ticket is drawn at random from them. What is the probability that the ticket drawn is a multiple of 3

3 / 20

Two dice are thrown simultaneously. What is the probability of getting two numbers whose product is even?

4 / 20

What is the Probability of getting a sum 9 from two throws of a dice

5 / 20

Two dice are rolled simultaneously. The probability that total score is prime number is

6 / 20

Let A and B be two mutually exclusive events with positive probability each, defined on the same sample space. Find the correct answer:

7 / 20

An unbiased coin is tossed until a head appears. The expected number of tosses required is

8 / 20

A card is drawn at random from an ordinary deck of cards. If an ace is drawn you win Rs. 100; if a king is drawn you win Rs. 75; if a queen is drawn you win Rs. 50; and if a jack is drawn you win Rs. 25. What is the probability of winning at least Rs. 25? What would you expect to win on average?

9 / 20

Among 25 articles, 9 are defective, 6 have only minor defects and 3 have major defects. The probability that, if a selected article is defective, then the defect is major is

10 / 20

A student must choose one of the subjects - Physics, Chemistry or Mathematics for study. She is equally likely to choose Physics or Chemistry and twice as likely to choose Mathematics. The probability that student chooses Mathematics is

11 / 20

If A and B are independent events, P(A) = 0.5, P(A U B) = 0.7, then P(B) is

12 / 20

A car with six spark plugs is known to have two defective spark plugs. If two plugs are pulled at random, then the probability that both are defective is :

13 / 20

If E(XY) = 36, E(X) = 9, E(Y) = 4 then

14 / 20

Events A and B are equally likely and are independent. The probability of the event A and B is 0.36. The probability of A is :

15 / 20

If P(A) = P(B) = p, then P[A ∩ B] 

16 / 20

Given P(A) = 0.5, P(B) = 0.4 if A and B are independent then P(A U B) is

17 / 20

If a fair coin is tossed twice, the probability of getting 'head' at least once is 

18 / 20

If two fair dice are tossed, the probability that the sum of the points on the dice equals 7 is 

19 / 20

If A and B are independent events then

20 / 20

Given P(A) = 0.4, P(A U B) = 0.7, and A and B are independent, P(B) is equal to

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The Lectures are as per Latest Syllabus for Academic Session 2022-23

Course Content of Our Video Lectures

Unit – I : Introduction & Overview

Chapter 1 : Population & Sample

Duration of Lectures : 113 Minutes

Based Upon J L Devore Chapter 1.1 & 1.2

Topics Covered

►Distinction between Population & Sample, Univariate Bivariate & Multivariate data, Descriptive & Inferential Statistics, Enumerative and Analytical Studies,

►Descriptive & Inferential Statistics,

►Stem & Leaf Displays,

►Dotplots,

►Histogram

Chapter 2 : Measures of Location

Duration of Lectures : 250 Minutes

Based Upon J L Devore Chapter 1.3

Topics Covered

►Frequency Series,

►Arithmetic Mean, Properties of Arithmetic Mean, Combined Mean, Corrected Mean,

►Median,

►Trimmed Median,

►Mode,

►Partition Values

Chapter 3 : Measures of Variability

Duration of Lectures : 203 Minutes

Based Upon J L Devore Chapter 1.4

Topics Covered

►Absolute and Relative Measures of Dispersion,

►Range & Coefficient of Range,

►Quartile Deviation & Coefficient of Quartile Deviation,

►Mean Deviation & Coefficient of Mean Deviation,

►Standard Deviation, Variance & Coefficient of Variation,

►Sample & Population Standard Deviation,

►Properties of Standard Deviation, Combined Standard Deviation,

►Fourth Spread & Outliers

Unit – 2 : Elementary Probability Theory

Chapter 4 : Probability

Duration of Lectures : 542 Minutes

Based Upon J L Devore Chapter 2

Based Upon Hogg, Tanis, Zimmerman Chapter 1

Topics Covered

►Sample Spaces and Events,

►Properties of Probability,

►Use of Permutations,

►Use of Combinations,

►Addition Theorem,

►Conditional Probability,

►The Multiplication Rule & Independent Events,

►Sampling with & without replacements,

►Law of Total Probability, Baye’s Theorem,

►Mathematical Expectation

Unit – 3 : Random Variables & Probability Distributions

Chapter 5 : Probability Distribution of Discrete Random Variables

Duration of Lectures : 312 Minutes

Based Upon J L Devore Chapter 3.1-3.3

Based Upon Hogg, Tanis, Zimmerman Chapter 2.1-2.2

Topics Covered

►Random Variables, Discrete & Continuous Random Variables,

►Probability Distribution for Discrete Random Variables,

►The Probability Mass Function (PMF), The Cumulative Distribution Function,

►Expected Values & Variance of a Discrete Random Variable,

►Properties of Expected Values & Variance of a Discrete Random Variable

Chapter 6 : Probability Distribution of Continuous Random Variables

Duration of Lectures : 312 Minutes

Based Upon J L Devore Chapter 4.1-4.2

Based Upon Hogg, Tanis, Zimmerman Chapter 3.1

Topics Covered

►Probability Distribution for Continuous Random Variables,

►The Probability Density Function (PDF), The Cumulative Distribution Function,

►The Percentiles of a Continuous Distribution,

►Expected Values & Variance of a Continuous Random Variable,

►Properties of Expected Values & Variance of a Continuous Random Variable

Unit – 4 : Special Probability Distributions

Chapter 7 : Special Discrete Distributions

Duration of Lectures : 314 Minutes

Based Upon J L Devore Chapter 3.4-3.6

Based Upon Hogg, Tanis, Zimmerman Chapter 2.4, 2.5 & 2.7

Topics Covered

►The Bernoulli Distribution,

►The Binomial Probability Distribution, Using Binomial Tables,

►Mean & Variance of a Binomial Distribution,

►The Hypergeometric Distribution,

►The Poisson Probability Distribution,

►Mean & Variance of a Poisson Distribution, The Poisson Process

Chapter 8 : Special Continuous Distributions

Duration of Lectures : 302 Minutes

Based Upon J L Devore Chapter 4.3-4.4

Based Upon Hogg, Tanis, Zimmerman Chapter 3.2-3.3

Topics Covered

►The Uniform Distribution,

►The Normal Distribution,

►The Standard Normal Distribution, Non Standard Normal Distribution,

►Approximating Binomial Distribution,

►The Percentiles of a Normal Distribution,

►The Exponential Distribution,

Unit – 5 : Random Sampling & Jointly Distributed Random Distributions

Chapter 9 : Jointly Distributed Random Variables

Duration of Lectures : 204 Minutes

Based Upon J L Devore Chapter 5.1-5.2

Based Upon Hogg, Tanis, Zimmerman Chapter 4.1-4.4

Topics Covered

►The Bivariate Distribution of Discrete Type,

►Joint Probability Mass Function, Marginal Probability Mass Function,

►The Conditional Probability Mass Function,

►The Bivariate Distribution of Continuous Type,

►Joint Probability Density Function, Marginal Probability Density Function,

►The Conditional Probability Density Function,

►Expected Values, Covariance and Correlation

Chapter 10 : Random Sampling

Duration of Lectures : 176 Minutes

Based Upon J L Devore Chapter 5.3, 5.4 & 5.5

Topics Covered

►Statistics & Their Distributions,

►The Distribution of Sample Mean,

►The Central Limit Theorem,

►The Distribution of a Linear Combination

End of Syllabus