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CHAPTER 14: POPULATION & SAMPLING PROCEDURES - Coggle Diagram
CHAPTER 14: POPULATION & SAMPLING PROCEDURES
Population
Successful statistical practice is based on focused problem definition
In sampling, this includes defining the population from which our sample is drawn :
Population can be defined as including all people or item.
Sampling Procedure
Define the population
Identify the sampling frame
Select a sampling procedure
Define the sample size
Select the sample units
Collect data from the sampled
Sampling Technique
Two forms of sampling used in research:
Non-probability
- Involve non-random selection of the sample
Probability sampling
Based on the concept of random selection
Non–Probability Sampling
-Convenience Sampling (Accidental or Haphazard)
The most common of all sampling techniques
Purposive Sampling
Sample respondent with purpose in mind
Judgemental sampling
Known as purposive sampling
Expert sampling
Involve the assembling of sample of respondent with known or demonstrable experience and expertise in some area
Probability Sampling
-Simple Random Sampling
This minimise bias and simplifies analysis results
Stratified random sampling
Involve dividing the population into subgroups based on variable known about those subgroup , and taking a simple random sample of each subgroup
Systematic sampling
Often used instead of random sampling
Cluster Sampling
The population divided into mutually exhaustive subsets
Multi-stage Sampling
Four method sampling techniques covered: simple, stratified, systematic and cluster are the simplest random sampling strategies.