(M) Sampling Methodology Flashcards
an act of studying or examining only a segment of the population to represent the whole.
SAMPLING
ADVANTAGE
● cheaper
● faster
● It has better quality of information
● It can obtain more comprehensive data
● It is the only possible method for destructive procedures
refers to the entire group of individuals of items of interest in the study.
POPULATION
the group from which representative information is desired and to which inferences will be made.
TARGET POPULATION
the population from which a sample will actually be taken
SAMPLING POPULATION
● a list of all the items in your population.
● It’s a complete list of everyone or everything you want to study.
● The difference between a population and a sampling frame is that the population is general and the frame is specific.
SAMPLING FRAME
an object or a person on which a measurement is actually taken, or an observation is made
ELEMENTARY UNIT OR ELEMENT
the difference between the value of the parameter being estimated and the estimate of this value based on the different samples.
SAMPLING ERROR
CRITERIA OF A GOOD SAMPLING DESIGN
- representative
- adequate
- practicality and feasibility
- economy and efficiency
The specific design that is best for a particular study
depends upon (4)
○ nature of the variables
○ population being studied
○ purpose for which the research is undertaken
○ availability of information relevant to the sampling procedure itself (e.g. sampling frame)
Two types of basic sampling design
Probability and Non-probability sampling designs
The probability of each member of the population to be selected in the sample is difficult to determine or cannot be
specified
NON-PROBABILITY SAMPLING DESIGNS
TYPES of NON-PROBABILITY SAMPLING DESIGNS
○ Judgment or purposive sampling
○ Accident or haphazard sampling
○ Quota sampling
○ Snowball technique sampling
○ Convenience sampling
○ Consecutive sampling
TYPES of NON-PROBABILITY SAMPLING DESIGNS
A. JUDGEMENT OR PURPOSIVE SAMPLING
B. ACCIDENT OR HAPHAZARD SAMPLING
C. QUOTA SAMPLING
D. SNOWBALL SAMPLING
E. CONVENIENCE SAMPLING
F. CONSECUTIVE SAMPLING
- Researchers select the samples based purely on the researcher’s knowledge and credibility.
- a sampling method that does not follow any systematic way of selecting participants
- To understand better about a population, the researcher will
need only a sample, not the entire population. Further, the researcher is interested in particular strata within
the population. - helps researchers find a sample when
they are difficult to locate. - Samples are selected from the population only because they
are conveniently available to the researcher. - Very similar to convenience sampling, with a slight variation. gives the researcher a chance to work with many topics and fine-tune his/her research by collecting results that have vital insights
ABCDEF
● The rules and procedures for selecting the sample and
estimating the parameters are explicitly and rigidly specified
● Each unit in the population has a known nonzero chance of
being included in the sample
PROBABILITY SAMPLING DESIGNS
PROBABILITY SAMPLING DESIGNS
A. SRS
B. Systematic sampling
C. Cluster sampling
D. Multi-stage sampling
E. STRATIFIED RANDOM SAMPLING
- When a sampling frame for the elementary units is not
readily available, or when cost considerations are important,
cluster sampling is often resorted to. - When the sample survey to be conducted has a wide coverage as in a nationwide surveys, a multi-stage sampling design is generally used.
- main characteristic is that every element in the population has an equal chance of being included in the sample
- A variation of SRS
- The population is first divided into non overlapping groups called strata. A simple random sampling is then selected from each stratum.
CDABE
PROBABILITY SAMPLING DESIGNS
Procedure:
1. Prepare a sampling frame (list of population elements).
2. Assign numbers to all elements.
3. Determine the required sample size.
4. Select random numbers using a lottery method or random number table.
5. The selected elements form the sample.
Advantages:
✔ Easy to draw samples.
✔ Simple data analysis.
Disadvantages:
✘ Costly if the sample is widely spread.
✘ High probability of obtaining an unrepresentative sample.
Simple Random Sampling (SRS)
PROBABILITY SAMPLING DESIGNS
Procedure:
1. Determine sample size and sampling interval (k = N/n).
2. Randomly select a starting number between 1 and k.
3. Include every k-th element in the sample.
Advantages:
✔ Easier to administer than SRS.
✔ A frame is not necessary.
✔ More precise estimates than SRS.
Disadvantages:
✘ Poor precision if population patterns exist.
Systematic sampling
PROBABILITY SAMPLING DESIGNS
Procedure:
1. Identify strata (non-overlapping subgroups).
2. Number population elements within each stratum.
3. Determine the required sample size for each stratum.
4. Select samples within strata using SRS.
Advantages:
✔ Greater precision than SRS.
✔ More efficient estimates.
Disadvantages:
✘ More complicated procedure.
Stratified Random Sampling
PROBABILITY SAMPLING DESIGNS
Procedure:
1. Divide the population into clusters.
2. Randomly select clusters.
3. Include all or some units from the chosen clusters.
Advantages:
✔ Requires only a list of clusters, not all units.
✔ Reduces costs of listing and transportation.
Disadvantages:
✘ May require a larger sample size.
✘ More difficult analysis.
Cluster sampling
PROBABILITY SAMPLING DESIGNS
Procedure:
1. Divide population into primary-stage units and select a sample.
2. Subdivide selected units into secondary-stage units and select another sample.
3. Continue the process until the final sampling stage is reached.
Advantages:
✔ More efficient and cost-effective for large populations.
✔ Does not require a full sampling frame.
Disadvantages:
✘ More complex design.
✘ Can lead to complicated analysis.
Multi-Stage Sampling
If no sampling was done and all elements were studied, it is called
TOTAL ENUMERATION
It is used if there is a very limited number of subjects and sampling may not be required, though it is a relatively rare condition.
TOTAL ENUMERATION
