Please enable JavaScript.
Coggle requires JavaScript to display documents.
Sampling- the statistical process of selecting a subset of a population of…
Sampling- the statistical process of selecting a subset of a population of interest for making observations and inferences about the population
The Sampling Process
Define the population as all people of a unit of analysis like certain persons, groups, organizations, country, objects, or anything you with to create an inference about
Sampling frame- is an accessible section of the target population, normally a list with contact information from where a sample can be drawn.
Probability Sampling
Probability sampling is a technique in which every unit in the population has a chance can be accurately determined
Simple random sampling, all possible subsets of a population are given an equal probability of being selected
Systematic sampling is ordered according to some criteria and elements are selected at regular intervals through that ordered list
Stratified sampling, the sampling frame is divided into homogeneous and non-overlapping subgroups called strata, and a simple random sample is drawn within each subgroup
Cluster sampling , dividing the population into clusters. Then randomly sample a few clusters, and measure all units within that cluster
Matched-pairs sampling, the comparing of two subgroups within one population based on a specific criterion
Multi-stage sampling- all they above examples are single stage sampling. In multi-stage sampling several of the above techniques are combined to generate a sample.
Non-Probability Sampling- a technique in which some units of the population have zero chance of selection or where the probability of selection cannot be accurately determined
Convenience sampling- accidental or opportunity sampling. A sample is drawn from that part of the population that is close to hand, readily available, or convenient
Quota sampling- the population is segmented into mutually-exclusive subgroups by stratified sampling and then a non-random set observation
Proportional quota sampling- the proportion of respondents in each subgroup should match that of the population
Non-proportional quota sampling- is less restrictive in that you don't have to achieve a proportional representation, but perhaps meet a minimum size in each subgroup
Expert sampling- is a technique where respondents are chosen in a non-random manner based on their expertise on the phenomenon being studied
Snowball sampling- you start by identifying a few respondents that match the criteria for inclusion in your study, and then ask them to recommend others they know who also meet your selection criteria
Statistics of Sampling
-
Frequency distribution- responses from different respondents to the same item or observation that can be graphed
Normal distribution- is the bell-shaped curve representing a large number of responses in a sample, frequency distribution
-
-
Sampling error- is the difference between two samples that differ from population parameters if the sample is not perfectly representative of the population
Sampling distribution- sampling representation of the estimated sample corresponding to the theoretical population parameter