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Introductory Statistics for Economics PDF Notes
Comprehensive Study Material for
Introductory Statistics for Economics
BA Economics (H) Delhi University, Students
Master the concepts of Histogram, Central Tendency, Measures of Variation, Probability and Probability Distributions such as Binomial, Poisson and Normal Distribution with professionally prepared PDF notes from Prime Academy.
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Demo Lectures of Introductory Statistics for Economics
Introductory Statistics for Economics, Demo Lectures, 2026 NEP, DU
Course Introduction
▾
Chapter 1 : Introduction & Overview (Includes Demo Lectures)
▾
▶ Population & Sample
▶ Histogram
Chapter 2 : Measures of Location
▾
Chapter 3 : Measures of Variability
▾
Chapter 4 : Theory of Probability (Includes Demo Lectures)
▾
▶ Probability Lecture 1
▶ Probability Lecture 2
▶ Probability Lecture 3
▶ Probability Lecture 4
Chapter 5 : Probability Distribution of Discrete Random Variables
▾
Chapter 6 : Probability Distribution of Continuous Random Variables
▾
Chapter 7 : Special Discrete Distributions
▾
Chapter 8 : Special Continuous Distributions
▾
Chapter 9 : Jointly Distributed Random Variables
▾
PYQ Solutions
▾
▶ 2025 Paper Q1 Solution
▶ 2024 Paper Q1 Solution
▶ 2024 Paper Q2 Solution
▶ 2023 Paper Q1 Solution
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Course Structure of Introductory Statistics for Economics
71 videos · 46h 05m · 6.4 GB
Course Introduction ▾
No content in this folder yet.
Unit 1 : Introduction & Overview ▾
Chapter 1 : Population & Sample ▾
1.1 Population and Sample
1.2 Histogram
1.3 Histogram
1.4 Histogram
1.5 Histogram
Chapter 2 : Measures of Location ▾
2.1Frequency Series
2.2 Arithmetic Mean
2.2a Properties of AM
2.3 Arithmetic Mean
2.4 Arithmetic Mean
2.5 Arithmetic Mean
2.6 Median
2.7 Trimmed Mean
2.8 Mode
2.9 Partition Values
Chapter 3 : Measures of Variability ▾
3.1 Range and QD
3.2 Standard Deviation
3.3 Standard Deviation
3.4 Standard Deviation
3.5 Standard Deviation
3.6 Standard Deviation Proofs
Unit 2 : Elementary Probability Theory ▾
Chapter 4 : Probability ▾
4.1 Probability Introduction
4.2 Odds in Favour
4.3 Probability
4.4 Use of Combinations
4.5 Permutations
4.6 Use of Permutations
4.7 Addition Theorem
4.8 Addition Theorem
4.9 Conditional Probability
4.10 Conditional Probability
4.11 Independent Events
4.12 Independent Events
4.13 Bayes Theorem
4.14 Expectations
4.15 Devore Section 2.2 Q11 to 19
4.16 Devore Section 2.3 Q29 to 32
4.17 Devore Section 2.3 Q33 to 37
4.18 Devore Section 2.4 Q45 to 49
Unit 3 : Random Variables and Probability Distributions ▾
Chapter 5 : Discrete Distributions ▾
5.1 Discrete Random Variable
5.2 PMF Graph
5.3 Discrete Distribution Questions
5.4 Devore Section 3.2 Q11 to 20
5.5 Devore Section 3.2 Q21 to 28
5.6 Devore Section 3.3
Chapter 6 : Continuous Distributions ▾
6.1 Continuous Distribution
6.2 PDF Graph
6.3 Devore Section 4.1 Q1 to 5
6.3a Section 14.1 Q6 to 10
6.4 Devore Section 4.2 Q11 to 15
Unit 4 : Special Probability Distributions ▾
Chapter 7 : Special Discrete Distributions ▾
7.1 Binomial Distribution
7.2 Hyper Geometric Distribution
7.3 Poisson Distribution
7.4 Poisson Distribution Questions
7.5 Doubts
Chapter 8 : Special Continuous Distributions ▾
8.1 Uniform Distribution
8.2 Normal Distribution
8.3 Normal Distribution
8.4 Normal Distribution
8.5 Normal Distribution
8.6 Exponential Distribution
8.7 Percentiles
Unit 5 : Random Sampling and Jointly Distributed Random Variables ▾
Chapter 9 : Joint Distrubution ▾
9.1 Joint PMF
9.2 Joint PDF
9.3 joint pdf
9.4 Correlation
9.5 Correlation
Chapter 10 : Sampling ▾
10.1 Samplng
10.2 Distribution of Sample Variance
10.3 Sampling
10.4 CLT
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