Statistical analysis depends heavily on how data is collected. Even correct calculations lead to misleading conclusions if the sampling procedure is poor. This lecture focuses on practical sampling methods and explains how they affect reliability, variability, and interpretation of results.

Sampling Procedure

A sampling procedure is the method used to select some units from a population for study.

The sampling procedure determines:

• Whether probability-based reasoning is valid
• How much random variation exists in results
• Whether conclusions can be generalized

Sampling is therefore both a practical and analytical decision.

Simple Random Sampling

In simple random sampling:

• Every individual in the population has the same chance of being selected
• Every possible sample of a given size is equally likely

This method allows uncertainty to be measured and controlled using probability.

Practical Interpretation

Suppose a population contains 2,000 students and a sample of 100 students is selected randomly.

• Each student has the same chance of selection
• The number of students selected from any department will vary randomly