Definition of Sampling Error
Sampling error is defined as the difference between:
- Two different samples from the same population
- The sample estimate and the corresponding population parameter — Correct Answer
- Primary data and secondary data
- Census data and survey data
Explanation:
Correct Answer Explanation
Sampling Error refers to the difference between the sample estimate and the corresponding population parameter (actual value of the characteristic).
Numerical Example:
- Population of 5 farmers with incomes: 500, 550, 600, 650, 700.
- Population average = (500+550+600+650+700) ÷ 5 = 600
- Sample of 2 farmers with incomes 500 and 600: Sample average = 550
- Sampling Error = 600 − 550 = 50
Key Points:
- Sampling error can be reduced by taking a larger sample.
- It is an inherent limitation of sample surveys.
- A population has two key characteristics: Central Tendency (mean, median, mode) and Dispersion (standard deviation, range).
📚 About this Topic — CH-2: Collection of Data
This multiple choice question is from CH-2: Collection of Data, NCERT Books, Statistics for Economics. It has 4 options with a detailed explanation of the correct answer. Practice more MCQs from CH-2: Collection of Data to strengthen your preparation.
