Sampling Methods

• Population: The entire group of individuals or objects being studied.

• Sample: A subset of the population selected for study.

• Census: A survey that collects data from every member of the population.

• Sample Survey: A survey that collects data from a sample of the population.

Sampling Methods

Random Sampling

• Definition: A method where every individual in the population has an equal chance of being selected.

• Advantages: Unbiased, representative of the population.

• Disadvantages: Can be time-consuming and expensive, especially for large populations.

• Example: Drawing names from a hat.

Specific Techniques for Random Sampling

1. Drawing Lots: Physically selecting individuals from a pool of potential participants.

2. Using Random Number Tables: Generating random numbers to select individuals from a list.

Systematic Sampling

• Definition: A method where individuals are selected from a list at regular intervals.

• Advantages: Simple and efficient.

• Disadvantages: Can be biased if there's a pattern in the list.

• Example: Selecting every 10th person on a list of students.

Stratified Random Sampling

• Definition: A method where the population is divided into subgroups (strata) and a random sample is taken from each stratum.

• Advantages: Ensures representation of different subgroups.

• Disadvantages: Can be complex to implement, especially if strata are not well-defined.

• Example: Dividing a school population into grade levels and selecting a random sample from each grade.

Non-Random Sampling

Cluster Sampling

• Definition: A method where the population is divided into clusters, and a random sample of clusters is selected.

• Advantages: Efficient for large, geographically dispersed populations.

• Disadvantages: Can be less representative than other methods.

• Example: Dividing a city into neighborhoods and selecting a random sample of neighborhoods.

Quota Sampling

• Definition: A method where a specific number of individuals are selected from each subgroup, often based on population proportions.

• Advantages: Ensures representation of different subgroups.

• Disadvantages: Prone to bias, as the selection of individuals within each subgroup is not random.

• Example: Selecting a specific number of male and female participants, regardless of other factors.

The choice of sampling method depends on various factors, including the research question, the population size, the desired level of precision, and available resources.