Please enable JavaScript.
Coggle requires JavaScript to display documents.
Sampling, (Matched -pairs: comparing two subgroups within one population…
Sampling
The Sampling Process
Sampling is the statistical process of selecting a subset of a population of interest for purpose of making observations and statistical inferences about the population
-
-
-
Matched -pairs: comparing two subgroups within one population based on specific criterion. An ideal way to understand bipolar differences between subgroups in a given population
Systematic: the sampling frame is ordered according to criteria and elements are selected at regular intervals through the ordered list. Begins with a random start and then proceeds with the selection of every kth element (k=N/n) sampling ration
Stratified: the sampling frame is divided into homogeneous and non-overlapping subgroups (called strata) and a simple random sample is drawn within each group. Can be non-proportional or proportional
Cluster:dividing the population into "clusters" because population is dispersed over wide geographic regions and randomly sample a few clusters and measure all units within the cluster
Multi-stage: combining single stage sampling techniques such as cluster sample a school district of a state and then simple random the schools and simple random a grade level
Simple Random: all possible subsets of a population are given an equal probability of being selected. The probability of selecting any set of n units out of a total N units in a sampling frame is NCn. Simplest probability sampling technique, sample is unbiased and inferences are most generalized
Expert : the technique where respondents are chosen in a nonrandom manner based on their expertise in the phenomenon being studied. Opinions from a sample of experts in more credible than sample including experts and nonexperts
Convenience :(accidental or opportunity sampling) a technique where a sample is drawn from part of the population that is close to hand, readily available or convenient. Most useful for pilot testing where goal is instrument testing or measurement validation
Snowball: Identify a few respondents that match the criteria for inclusion in study and then ask them to recommend others they know who also meet selection criteria. Can be the only way to reach hard to reach populations or when no sampling frame is available
Quota: the population is segmented into mutually exclusive subgroups (just like stratified sampling) and a non-random set of observations is chosen from each subgroup to meet predefined quota
-
Sampling distribution is the true representation of the population with the estimated sample statistics identical to the theoretical population parameters. It is plotted on a frequency histogram. Tend to have more sample statistics clustered around the mean
Frequency distribution is the graph of responses from different respondents based on their frequency of occurrence. For large number of responses in a sample, it can resemble a bell shaped curve, normal distribution (sample mean or standard deviation) of overall characteristics of entire sample
Confidence interval is the estimated probability that a population parameter is within a specific interval of sample statistic values. Normal distributions tend to follow 68-95-99 percent rule
Non-proportional quota: less restrictive sampling where proportional representation is not achieved, but a minimum size in each subgroup
-
the technique in which every unit in the population has a chance (non-zero probability) of being selected in the sample. All probability sampling have two attributes in common: every unit in population has a known non-zero probability and sampling procedure involves random selection
-
A technique in which some units of population have zero chance of selection or where probability of selection cannon accurately be determined
-