⚠️What are the main sources of errors in Sampling Surveys?

⚠️What are the main sources of errors in Sampling Surveys?

Answer: Errors in sample surveys arise mainly due to two broad causes — sampling errors and non-sampling errors.

1. Sampling Errors:

These occur because only a sample (not the whole population) is studied.Different samples give slightly different estimates even when drawn from the same population.

Examples:

• Different samples giving different average incomes.

• Sample mean differing from true population mean.

How to Reduce:

• Increase sample size.

• Use efficient designs (e.g., stratified or systematic sampling).

2. Non-Sampling Errors:

These are not related to sample size and can occur even in a census.

Main Sources:

1. Measurement Error: Wrong responses or recording mistakes.

2. Non-Response Error: Some selected units do not respond.

3. Processing Error: Mistakes in coding, editing, or data entry.

4. Frame Error: Incomplete or outdated frame.

5. Interviewer Bias: Leading questions or poor training.

How to Reduce:

• Proper training and supervision.

• Pilot surveys and quality checks.

• Double data entry and validation.

Example (Indian Context): In PLFS, non-sampling errors may occur due to incorrect occupation coding or skipped questions, while sampling errors arise due to limited sample size in certain states.

Follow-up Question:

👉 Which type of error is more dangerous?

→ Non-sampling errors, because they introduce bias that cannot be reduced by increasing sample size.