Please enable JavaScript.
Coggle requires JavaScript to display documents.
Sampling Designs - Coggle Diagram
Sampling Designs
Basic Concepts:
Population: The entire set of elements (subjects, participants, respondents, cases) the researcher is interested in.
Target Population: The specific, ideal group the researcher wants to generalize results to (e.g., all Egyptian HCV patients in 2022).
Accessible Population: The group that is actually available and from which the sample is drawn (e.g., all HCV patients in a specific university hospital in 2022).
-
-
Sampling Frame: A list of all elements in the population from which the sample is drawn (e.g., a telephone book, a patient registry).
Sample Size: The number of members in the sample. Larger samples are generally more representative and have smaller sampling error.
Sampling Error: The natural difference between the characteristics of the sample and the characteristics of the population it came from.
Eligibility Criteria: Rules that define who can (inclusion criteria) or cannot (exclusion criteria) participate in the study.
Sampling Bias: A systematic tendency to select units with particular characteristics, making the sample unrepresentative.
Strata: Mutually exclusive segments of a population based on specific characteristics (e.g., age groups, income brackets).
-
-
Purpose of Sampling:
Saves time, money, and effort. Increases research efficiency. Makes studying large populations feasible.