Sampling Techniques Notes PDF

Sampling Techniques Notes Probability Sampling  Simple Random Sampling: Every individual in the population has an equal chance of being selected.  Stratified Sampling: The population is divided into subgroups (strata) based on specific characteristics, and then a random sample...

Sampling Techniques Notes Probability Sampling  Simple Random Sampling: Every individual in the population has an equal chance of being selected.  Stratified Sampling: The population is divided into subgroups (strata) based on specific characteristics, and then a random sample is drawn from each stratum.  Systematic Sampling: Individuals are selected at regular intervals from a numbered list.  Cluster Sampling: The population is divided into clusters (groups), and a random sample of clusters is selected. All individuals within the selected clusters are included in the sample. Non-Probability Sampling  Convenience Sampling: Individuals are selected based on their availability or ease of access.  Quota Sampling: A predetermined number of individuals from each subgroup is selected, regardless of their probability of being chosen.  Purposive Sampling: Individuals are selected based on specific criteria or characteristics relevant to the study.  Snowball Sampling: Participants are asked to refer others who meet the study criteria. Random Sampling:  Can be used on both small and large populations. Random sampling ensures that every individual in the population has an equal chance of being selected, regardless of the population size. Non-Random Sampling:  Level of bias varies: Non-random sampling methods can introduce bias, which can affect the representativeness and generalizability of the sample. The level of bias depends on several factors, including: o Convenience Sampling: High bias, as the sample may not be representative of the entire population. o Quota Sampling: Moderate bias, as the sample may be biased towards certain subgroups. o Purposive Sampling: Low bias if the selection criteria are carefully chosen to ensure representativeness. o Snowball Sampling: Moderate to high bias, as the sample may be biased towards individuals connected to the initial participants.