Sampling is that part of statistical practice concerned with the selection of an unbiased or random subset of individual observations within a population of individuals intended to yield some knowledge about the population of concern, especially for making predictions based on the statistical inference (Ader, Mellenberg & Hand: 2008). There are quite a number of sampling methods that can be employed in research and these include simple random sampling, systematic sampling, stratified sampling, cluster sampling, matched random sampling, quota sampling, convenience sampling, line intercept sampling, to mention just a few.

Simple Random Sampling:
In a simple random sample of a given size (elements are randomly chosen until a desired sample size is obtained), all such subsets of the frame are given an equal chance or probability. Each element of the population thus has an equal probability of selection: the frame is not subdivided or partitioned. Furthermore, any given pair of elements has the same chance of selection as any other pair and similarly for triples, quads and so on. This minimizes the bias and simplifies analysis of the results. However, simple random sampling method can be vulnerable to sampling error because the randomness of the selection may result in a sample that does not reflect the makeup of the population, for instance, a simple random of ten people from a given town will on average produce five men and five women, but any give trial is likely to over-represent one sex and under-represent the other thus leading to bias misrepresentation of what is actually happening on the ground. Simple random sampling may also be cumbersome and tedious when sampling from an unusually large target population…………(add)

Systematic Sampling:
Systematic sampling relies on arranging the target population according to some ordering scheme and then selecting elements at regular intervals through that ordered list. Systematic sampling involves a...

...Types of Sampling
In applications:
Probability Sampling: Simple RandomSampling, StratifiedRandomSampling, Multi-Stage Sampling
* What is each and how is it done?
* How do we decide which to use?
* How do we analyze the results differently depending on the type of sampling?
Non-probability Sampling: Why don't we use non-probability...

...SAMPLING TECHINIQUE
PROBABILITY SAMPLING
Having chosen a suitable sampling frame and established the actual sample size required, you need to select the most appropriate sampling technique to obtain a representative sample. The basic principle of probability sampling is that elements are randomly selected in a population. This ensures that bias is avoided in the identification of the elements. It is an efficient method...

...MAUREEN L. M.
INTERMEDIATE MICROECONOMICS
SAMPLING TECHNIQUES
INTRODUCTION
A sample is a unit or subset of selection from a larger population that is used in studying to draw conclusions regarding the whole population. A sample is usually selected from the population because it is not easy to study the entire population at once and the cost of doing so may be very high. The sample should be the best representation of the whole population to enable accurate...

...Simple random sample (SRS)
In statistics, a simple random sample from a population is a sample chosen randomly, so that each possible sample has the same probability of being chosen. One consequence is that each member of the population has the same probability of being chosen as any other. In small populations such sampling is typically done "without replacement", i.e., one deliberately avoids choosing any member of the population more than once....

...characteristic of a sample.
A number that can be computed from data, involving no unknown parameters. As a function of a random sample, a statistic is a random variable. Statistics are used to estimate parameters, and to test hypotheses.
Survey:
Study of only a portion of the population
Census Survey
Study of certain characteristics of every element of a population.
Sampling Survey
Making inferences with a sample.
Nominal Scale
Observed...

...
Sampling methodologies
Sampling
It may be defined as a process of selecting units that may be people, organizations etc, from a larger whole i.e. from a population of interest, so that by studying the sample we may come up with general characteristics of the entire population under consideration.
Types of sampling methods:
Probability sampling
Probability sampling is a type of...

...Please write down four factors which affect sampling error and for each factor, write down the effect of sampling error (i.e., if a factor is up, then what happens to the sampling error)
8. Please write down four factors to decide sample size and for each factor, write down the effect of sample size (i.e., if a factor is up, then what happens to the sample size)
9. Please write down when the systematic sampling is better than...

...Sampling is concerned with the selection of a subset of individuals from within a statistical population to estimate characteristics of the whole population. Acceptance sampling is used to determine if a production lot of material meets the governing specifications. Two advantages of sampling are that the cost is lower and data collection is faster than measuring the entire population.
Sampling is the process of selecting units (e.g.,...

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