Is a part of population that is chosen as representatives of the entire population
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 Which type of sample is representative of the entire population?A representative sample is a sample from a larger group that accurately represents the characteristics of a larger population. It's known as a representative sample because the answers obtained from it accurately reflect the results you would achieve by interviewing the entire population.
Is the method of getting sample?There are two types of sampling methods: Probability sampling involves random selection, allowing you to make strong statistical inferences about the whole group. Non-probability sampling involves non-random selection based on convenience or other criteria, allowing you to easily collect data.
What does it mean when a part of the population is under representative?An underrepresented population refers to a subgroup of the population whose representation is disproportionately low relative to their numbers in the general population, or in the case of clinical trials or patient registries, disease population.
What is the study of an entire population called?A study of the entire population is called a census. However, performing a census is usually impractical, expensive and time-consuming, if not downright impossible. Therefore, nearly all statistical studies are based on a subset of the population, which we will call the sample.
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