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1.0 Sampling is a process used in statistical analysis in which a predetermined number of observations are taken from a larger population. In simpler words, Sampling is the process of how a researcher chooses his/her sample from a larger group.

1.1 Convenient Sampling
Selecting samples/participants from those people you get the easiest access to.

1.2 Stratified Sampling
Dividing a large group into a few smaller groups (strata), and selecting the final samples/participants proportionally from every stratum.

1.3 Cluster Sampling
Quite similar to Stratified Sampling. A large group will be divided into smaller groups (clusters), and a few clusters will be selected as the final samples/participants.

1.4 Random Sampling
Everyone has the same percentage of confirmation to be chosen as the sample/participant.

1.5 Quota Sampling
A sampling method of gathering representative data from a group.

2. Realibility is the consistency of the result even after being measured over time.

3. Validity can be summarized as how well a test is measuring what it was designed to measure.

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Nur Farhana Binti Farid Rizal (GS 51250)

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Nur Farhana Binti Farid Rizal (GS 51250)

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Reliability
A way of assessing the quality of the measurement procedure to collect data in dessertation.

Validity
A test or instrumet is accurately measuring what it is supposed to.

Types of sampling
1. Convinience - Selecting subjects that are easy to get
2. Purposive - A specific group is chosen which is relevant to the criteria that fits the research questions
3. Snowball - Also known as chain sampling, which is a study of subjects recruit future subjects among their acquaintance.
4. Random - Each sample has an equal probability of being chosen.

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Reliability
Consistency of the result after been tested many times.
Validity
It measures what is supposed to measure.
Sampling
1. Purposive Sampling
A specific target group is choose that is relevant to the criteria that fits the research question.
2. Convenience Sampling
Selecting participants that are easy access.
3. Snowball sampling
uses existing participants or contacts to reach their social networks and refer the researcher to other potential participants.
4. Random Sampling
Everyone has the chance to be selected as a participant.

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Sampling
1. Convenience sampling: is a sampling technique where the participants are selected because of convenience. For example, looking for respondents by waiting at the escalator in a shopping complex.
2. Purposive sampling: is a sampling technique that is selected based on population and the objective of the study. For example, if the study is carried out on students from Indonesia, students who are not from Indonesia will not be selected.
3. Random sampling: is a sampling technique which everyone will have the chance to be chosen. It is unbiased.
4. Stratified sampling: population is divided into groups called strata. A simple random sample is drawn from each group. The sample is created out of the random selection of elements from all the strata.
5. Cluster sampling: population is divided into different groups called clusters. A random sample of clusters is selected from the population. All the units of the randomly selected clusters form a sample.
6. Quota sampling: is a sampling technique  of gathering representative data from a group.

Reliability
Reliability is the consistency of the results being measured over time.

Validity
Validity is the instrument is measuring what it was designed to measure.

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Case Study of Sampling: there are three universities in Malaysia where I think it is potentially considered as research sites. 100 respondents from three universities will be as research samples. The question are, why I need three universities, why not only 1 or 2, or more than 4, etc? Or, Why I need 100 respondents? What happened if I just got 50, do I need to add more respondents, etc? What kind of sampling I should choose for this situation?

SAMPLING

Sampling is a method how you select the research site and respondent. Before you decide the sampling for your research, picturing or drawing the research site (s) and respondent (s) would be helpful SAMPLE: small group to observe/interview. POPULATION: the larger group. SAMPLE is a portion of a POPULATION).

Two Major types of sampling procedures:

1. Probability Sampling: all has an equal chance to select.

a. Simple Random Sampling: The best known sampling. For example, 100 students from the population attending UPM.

b.Stratified sampling: number of subgroups, or strata. For example, to assess opinions on a certain political issues.

c. Cluster sampling: put the subject in groups or cluster, for example, the use of intact classrooms as clusters.

d. Systematic sampling: drawing a sample by taking every K-th, for example, language testing.

2. Non-probability Sampling: no assurance of all elements to be included.

a. Convenience sampling: the weakest of all sampling procedures, for example, using a large undergraduate class, etc.

b. Purposive (judgement) sampling: judged to be typical, or representative, for example, forecasting national elections.

VALIDITY and RELIABILITY

Validity and Reliability: criteria for measuring devices.

1. Validity: the extent to which theory and evidence support the proposed interpretations of test scores for an intended purpose.

2Reliability: how consistently a test or an instrument measures what is purports to measure.

Source: (Walker, et al., (2014). Introduction to Research in Education (9th ed). Belmont, CA: Wadsworth Cengage Learning.).

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Reliability: quality of measurement based on consistency -
If the variables remain the same, can the same instrument produce same/similar (consistent) results when used repeatedly? Can it be considered as flawed if the results produced are not related/too dissimilar.

Validity: accuracy of measurement - has credibility and believability (how well the instrument measures what it is intended to measure)
The scores or results produced are related to the variable.

Sampling means selecting units to represent the whole population that are of interest to be studied.

Main types of sampling:

1. Probability - occur at random to ensure all members of population has a chance to be selected

2. Non-probability - not random, based on convenience or voluntary. Avoid sampling bias.

Probability sampling methods:
(Refer Elia's and Mona's explanation for examples)

Random

Stratified random - population are divided into strata based on criteria that may influence the variables. Random sampling is done within the strata.  [subsections of population]

Cluster

Systematic

** Need to distinguish between stratified and cluster sampling.

Non-probability sampling methods:

Convenience

Purposive

Snowball

Quota - quotas are created based on specific qualities.

Qualitative sampling differs based on the criteria needed to suit the study.

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Types of Sampling
1. Systematic Sampling: Often used to select a specified number of records from a computer file.
2. Convenience Sampling: Usually used in exploratory research where the researcher is interested in getting an inexpensive approximation of the truth.
3. Random Sampling: Probability Sampling. Each person has fair chances to be selected.
4. Purposive sampling : A non-representative subset of some larger population, and is constructed to serve a very specific need or purpose.
5. Judgment sampling: A common non-probability method. The researcher selects the sample based on judgment. This is usually and extension of convenience sampling.

Reliability and Validity

Reliability is the degree to which an assessment tool produces stable and consistent results.

Validity refers to how well a test measures what it is purported to measure.

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Good job, Mona. What about other's opinion? There are other types of sampling methods too.

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Sampling Types:

*Random sampling: Population are sampled randomly, for exaple, walk past a shop are sampled.
*Systematic Sampling: Chosen on the basis of an ordered system, for example, you wanted to sample 150 children from a school of 1,500, you would take every 10th name.
*Opportunity Sampling: The sample taken is chosen at one place ate one time, therefore those people present at that time are sampled
*Cluster Sampling: Population divided into units each containing individuals in a range of circumstances, for example, neighborhoods or school districts.

What is reliability and validity?
Validity: accuracy of measurement. Is the instrument appropriate for what needs to be measured?
Reliablility: consistency of measurement. Does the instrument yield consistent results?