Sample:
In statistics, a sample is a subset of individuals or observations selected from a larger population.

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The purpose of sampling is to make inferences about the population based on the characteristics observed in the sample. Sampling is a practical approach when studying an entire population is not feasible due to constraints such as time, cost, or logistics.

Example:
Imagine you want to determine the average height of students in a large university. Instead of measuring the height of every student (which may be impractical), you could select a representative group, say 100 students, and measure their heights. This subset of 100 students constitutes your sample. By analyzing the heights of these students, you aim to make an inference about the average height of the entire university population.

Two Types of Sampling Techniques:

Random Sampling:

Definition: In random sampling, every individual or element in the population has an equal chance of being selected for the sample. This method helps ensure that the sample is representative and unbiased.
Example: Suppose you have a list of all students in a school, and you use a random number generator to select 50 students from this list. Each student has an equal probability of being chosen.

Stratified Sampling:

Definition: Stratified sampling involves dividing the population into subgroups or strata based on certain characteristics, and then randomly sampling from each subgroup. This ensures that each subgroup is adequately represented in the sample.
Example: If you want to study the academic performance of students in a school, you might first classify them into strata based on grade levels (e.g., freshmen, sophomores, juniors, seniors). Then, within each stratum, you randomly select a proportionate number of students for your sample.

These sampling techniques help researchers obtain reliable and meaningful insights from a smaller subset of a population, making statistical analysis more manageable and cost-effective. The choice of sampling method depends on the research objectives and the characteristics of the population being studied.