Bonjour everyone..
This is my first summary of the presentation one. I make it more to short form or short notes as i have gone through our textbook. There are few questions that we should focus in this topic.
How to distinguish between a sample and a population? What is representative sample? What is meant by 'systematic sampling', 'convenience sampling' and 'purposive sampling'? All these questions can be answered by the end of this summary. Sub topic that will be covered under this 'Research Design- Sampling' are
This is my first summary of the presentation one. I make it more to short form or short notes as i have gone through our textbook. There are few questions that we should focus in this topic.
How to distinguish between a sample and a population? What is representative sample? What is meant by 'systematic sampling', 'convenience sampling' and 'purposive sampling'? All these questions can be answered by the end of this summary. Sub topic that will be covered under this 'Research Design- Sampling' are
1) What is sample?
2) Random sampling methods
3) Nonrandom sampling methods
4) Sample size
5) External validity: Generalizing from a sample
1) What is sample?
A sample is a finite part of a statistical population whose properties are studied to gain information about the whole (Webster, 1985). When dealing with people, it can be defined as a set of respondents (people) selected from a larger population for the purpose of a survey.
What is population?
A population is a group of individuals, persons, objects, or items from which samples are taken for measurement for example a population of presidents or professors, books or students.
What is sampling?
2) Random sampling methods
Random Sampling
The dean of a school of education in a large midwestern university wishes to find out how her faculty feel about the current sabbatical leave requirements at the university. She places all 150 names of the faculty in a hat, mixes them thoroughly, and then draws out the names of 25 individuals to interview. There are four types of random sampling methods.
a) Simple sampling methods
a) Simple sampling methods
Each and every member of the population has an equal and independent chance of being selected. Best way to use when the sample is large – devised to obtain a sample representative of the population of interest.The key to obtaining a random sample is to ensure that each number of population has an equal chance of being selected. The advantage of simple sampling is if large enough, it is likely to produce a representative sample. Meanwhile the disadvantage is it not easy to do. Each member of the population must be identified.
b) Stratified random sampling
Stratified Random Sampling is a process where certain subgroups (strata) are selected for a sample in a same proportion as they exist in the population. The new principal of a private school wants to know her 2nd grade students response to a new system that she implemented last year. She intends to compare the achievement of the students before and after she came in. She thinks that gender plays an important variable that may effect the outcome of her study, so she adds in the proportion of males and females in the study is the same as in the population. The advantage is it increases the likelihood of representativeness especially if one's sample is not very large.
c) Cluster random sampling
A subject rather than individuals is known as cluster random sampling. It is more effective with large numbers of clusters.
d) Two-stage random sampling
Often useful to combine cluster random sampling with individual random sampling.
3) Nonrandom sampling methods
The purpose of this method is to make an explicit choice based on our own judgement
about exactly whom to include in the sample. When random sampling is not possible,
then we may choose the following :
Systematic Sampling
- every nth individual in the population list is selected for inclusion in the sample.
Convenience Sampling
a group of individuals who (conveniently) are available for study.
Purposive Sampling
Selection of samples are based on the researchers’ judgment that the samples could
contribute to the research in providing the information for the data better as they are
the involved party in the research matter itself. The power of purposive sampling lies
in selecting information rich cases for in-depth analysis related to the central
issues being studied.
5) Sample size
- a sample should be as large as the researcher could obtain with a reasonable expenditure of time and energy.
6) External validity: Generalizing from a sample
a) population generalizability: refers to the degree to which a sample represents the population of interest. The finding will be limited if the results of a study only apply to the group being studied and if that group is small.
b) ecological generalizability: refers to the degree to which the result of the study can be extended to other settings or conditions. The researchers must make clear the nature of the environment conditions.
more elaborations and explanations can be referred in HOW TO DESIGN AND EVALUATE RESEARCH IN EDUCATION by Fraenkel, Wallen and Hyun (8th edition).
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