Types of Sampling Methods

Definition: Random sampling (also known as sample random sampling) is a technique where a sample is chosen such that every element in the population has an equal chance of being selected.

Numbering Strategy: Each individual element of the population is assigned a sequential number.
Selection Rule: A sample is obtained by selecting every $k^{\text{th}}$ element throughout the population, where $k$ represents a defined numerical step.
Initial Value Selection: The first selected element corresponds to a randomly chosen number located between $1$ and $k$ .
Characteristics and Usage: Systematic sampling is considered the easiest method of sampling and is primarily employed when obtaining a pure random sample is unobtainable.

Population Segregation: Stratified sampling is utilized when populations are partitioned or segregated into subgroups or strata based on specific characteristics.
Categorization Attributes: Strata are organized according to distinct attributes, such as race or gender.
Sampling Procedure: A separate random sample is systematically extracted from each individual stratum.
Sample Sufficiency: Sampling from each stratum guarantees that the overall representation from each subgroup will be large enough to provide useful data.