It is a subset taken from a population either by random or non-random sampling techniques
How do we study a population? Show It is important to note that whether a census or a sample is used, both provide information that can be used to draw conclusions about the whole population. What is a census (complete
enumeration)? What is a sample (partial enumeration)? Information from the sampled units is used to estimate the characteristics for the entire population of interest. When to use a census or a sample?
How are samples selected? A sample must be robust in its design and large enough to provide a reliable representation of the whole population. Aspects to be considered when designing a sample include the level of accuracy required, cost, and the timing. Sampling can be random or non-random. In a random (or probability) sample each unit in the population has a chance of being selected, and this probability can be accurately determined. Probability or random sampling includes, but is not limited to, simple random sampling, systematic sampling, and stratified sampling. Random sampling makes it possible to produce population estimates from the data obtained from the units included in the sample. Simple random sample: All members of the sample are chosen at random and have the same chance of being in the sample. A lottery draw is a good example of simple random sampling where the numbers are randomly generated from a defined range of numbers (i.e. 1 through to 45) with each number having an equal chance of being selected. Systematic random sample: The first member of the sample is chosen at random then the other members of the sample are taken at intervals (i.e. every 4th unit). Stratified random sample: Relevant subgroups from within the population are identified and random samples are selected from within each strata. In a non-random (or non-probability) sample some units of the population have no chance of selection, the selection is non-random, or the probability of their selection can not be determined. In this method the sampling error cannot be estimated, making it difficult to infer population estimates from the sample. Non-random sampling includes convenience sampling, purposive sampling, quota sampling, and volunteer sampling Convenience sampling: Units are chosen based on their ease of access; Purposive sampling: The sample is chosen based on what the researcher thinks is appropriate for the study; Quota sampling: The researcher can select units as they choose, as long as they reach a defined quota; and Volunteer sampling: participants volunteer to be a part of the survey (a common method used for internet based opinion surveys where there is no control over how many or who votes). Collecting data about a population flowchart:
Recommended: Read Data Sources next Return to Statistical Language Homepage Further information: External links: Basic Survey Design: Samples and Censuses What is the subset taken from a population called?A sample is a subset of units in a population, selected to represent all units in a population of interest. It is a partial enumeration because it is a count from part of the population. Information from the sampled units is used to estimate the characteristics for the entire population of interest.
What sampling technique in which members of the population are listed and samples are selected in intervals called sample intervals?Systematic sampling is a type of probability sampling method in which sample members from a larger population are selected according to a random starting point but with a fixed, periodic interval. This interval, called the sampling interval, is calculated by dividing the population size by the desired sample size.
Is a subset taken from the population?A sample refers to a smaller, manageable version of a larger group. It is a subset containing the characteristics of a larger population. Samples are used in statistical testing when population sizes are too large for the test to include all possible members or observations.
What is random sampling and nonDefinition. Random sampling is a sampling technique where each sample has an equal probability of getting selected. Non-random sampling is a sampling technique where the sample selected will be based on factors such as convenience, judgement and experience of the researcher and not on probability.
|