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Describe how more complex probability sampling techniques could provide samples more representative of a target population than simple random sampling Illustrate your answer with an information technology example.

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Probability sampling is used to select a sample from a population in such a way that every individual or element in the population has a known and non-zero chance of being selected. This method ensures that the sample is representative of the population, allowing for generalizations and statistical inferences to be made with greater validity and accuracy. Probability sampling techniques include simple random sampling, stratified sampling, cluster sampling, and systematic sampling.


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The process of selecting representative elements from a population is called sampling. Sampling involves selecting a subset of individuals or items from a larger group in order to draw conclusions or make inferences about the entire population. Various sampling techniques, such as random sampling or stratified sampling, can be utilized to ensure that the selected elements accurately represent the population characteristics.


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Sampling techniques in researching involves to types of sampling. The probability sampling and the non-probability sampling. Simple random is an example of probability sampling.


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The techniques used to estimate characteristics of a population based on a sample are called statistical inference methods. These methods include point estimation, confidence intervals, and hypothesis testing. They allow researchers to draw conclusions about a population's parameters from the data collected in a smaller, representative sample. Common techniques involve using measures like the sample mean or proportion to infer about the population mean or proportion.


Non -probability sample techniques?

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