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Understanding Population and Sample in Psychological Research

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Understanding populations and samples is crucial in psychological studies for valid results. A population encompasses all individuals of interest, while a sample is a subset used for the study. Sampling techniques, like random sampling, aim to ensure representativeness and minimize bias, allowing researchers to generalize findings to the whole population. Challenges in data collection from large populations necessitate strategic sampling for meaningful insights.

Distinguishing Populations and Samples in Psychological Studies

Psychological research necessitates a clear understanding of the terms 'population' and 'sample' to ensure the validity of study results. A population is the entire set of individuals or observations that are of interest to the researcher's question. For instance, if a study aims to understand the mental health of teenagers in a particular country, then all teenagers in that country would be considered the population. However, it is often impractical to study the entire population due to resource constraints. Therefore, researchers select a sample, which is a smaller group drawn from the population. The sample must be representative, meaning it should reflect the population's diversity, to allow for the extrapolation of the study's findings to the entire population.
Diverse group of people in an open space with some in the foreground reading, talking and playing, in a natural and sunny environment.

Sampling Techniques and Their Significance

The process of selecting a sample from a population is known as sampling, and the method used can significantly impact the study's outcomes. There are several sampling techniques, with probability sampling, including random sampling, being the gold standard. Probability sampling allows for each member of the population to have a known and usually equal chance of being included in the sample. This can be achieved through lottery systems or computerized random number generators. Such methods help to minimize selection bias, increasing the likelihood that the sample will be representative. Non-probability sampling methods, such as convenience sampling or quota sampling, are sometimes used but may introduce bias and limit the generalizability of the results.

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Definition of 'population' in research

Entire set of individuals or observations relevant to the research question.

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Definition of 'sample' in research

A smaller group from the population, used for practical study due to resource limits.

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Criteria for a representative sample

Sample must mirror population diversity to generalize findings to the whole population.

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