Sampling theorem in statistics

The sampling theorem in statistics states that to accurately understand an entire population, a representative subset (sample) must be large and diverse enough so that its characteristics reflect the whole. This means selecting a sample that captures the population’s variability ensures conclusions drawn from the sample apply broadly. Proper sampling avoids biases and helps us make reliable inferences without studying every individual, making data collection more efficient while maintaining accuracy.