📊 Why do we prefer Sampling in large-scale statistical investigations?

📊 Why do we prefer Sampling in large-scale statistical investigations?

Answer: Sampling is preferred in large-scale investigations because it provides quick, economical, and practical results without compromising reliability.

Main Reasons:

1. Economy of Resources: Conducting a census on millions of units requires huge manpower, cost, and time. Sampling reduces this burden.

2. Speed: Sampling allows faster data collection and analysis — critical when decisions are time-sensitive (e.g., inflation, unemployment).

3. Feasibility: For large or infinite populations (like rainfall readings, or daily electricity usage), complete enumeration is impossible.

4. Accuracy in Practice: If designed carefully, sampling can provide more accurate results than a poorly conducted census.

5. Destructiveness Avoided: In industries, sampling allows quality testing without destroying the entire lot (e.g., bulb testing, food testing).

Example: The National Family Health Survey (NFHS) collects data from a few lakh households to represent more than 130 crore people of India — saving huge resources.

Follow-up Question: 👉 Is sampling always better than census?

→ Not always. Sampling is better for estimation, but census is required when every individual count is necessary (like population enumeration).