🎯 What is Sampling Error? How does it differ from Non-Sampling Error?

🎯 What is Sampling Error? How does it differ from Non-Sampling Error?

Answer: Sampling Error: It arises because only a part (sample) of the population is studied. Different samples drawn from the same population will give slightly different estimates.✅ Can be reduced by increasing sample size or using efficient designs.

Non-Sampling Error: It arises from causes other than sampling, such as:

• Measurement error

• Response bias or non-response

• Wrong data entry or tabulation

• Interviewer’s mistake

✅ Cannot be reduced just by increasing sample size; must be controlled by training, supervision, and questionnaire design.

Example: If we select 100 households at random, variation in their income estimate = sampling error. But if 20 households refuse to respond or data is entered wrongly = non-sampling error.

Follow-up: Which error can be controlled by increasing sample size?

→ Only sampling error decreases as sample size increases (∝ 1/√n).Non-sampling errors remain unaffected or may even increase.