SAMPLE SIZE Meaning and
Definition
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Sample size refers to the number of observations or individuals included in a study or research project. It is a critical component in statistical analysis, as it directly influences the accuracy and reliability of the findings or conclusions drawn from the study. The sample size is determined based on various factors, such as the research objectives, population size, desired level of confidence, and expected effect size.
In quantitative research studies, a larger sample size is generally preferred, as it allows for greater precision and reduces the chances of bias. A larger sample provides a more representative representation of the population, increasing the generalizability and external validity of the study's results. Conversely, a smaller sample size may limit the ability to make accurate inferences about the population from which the sample is drawn.
Determining the appropriate sample size involves statistical calculations that ensure there is a sufficient number of observations to detect and interpret meaningful relationships or differences between variables. This is particularly important in hypothesis testing, where the sample size affects the statistical power of the study.
Researchers often employ statistical methods like power analysis to estimate the required sample size. This analysis considers factors like the desired level of significance, effect size, and statistical power to determine the minimum sample size needed to achieve reliable results.
Overall, sample size is a critical consideration in research methodology, as it directly impacts the validity and generalizability of study findings. Choosing an appropriate sample size is essential for ensuring the study's conclusions accurately represent the target population and allowing for valid statistical analysis.
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Etymology of SAMPLE SIZE
The term "sample size" emerged from the field of statistics, which refers to the branch of mathematics that deals with the collection, analysis, interpretation, presentation, and organization of data. The etymology of "sample size" can be understood by examining the derivation of its individual components.
1. Sample: The term "sample" originates from the Old French word "essample", meaning "example" or "model". It further comes from the Latin word "exemplum", which carries the same meaning. Over time, "sample" evolved to refer to a representative portion or subset of a larger population. In statistics, a sample is a subset of individuals or observations drawn from a larger population to represent it in a study or analysis.
2. Size: The word "size" has its roots in the Old French word "sise", which denoted "an allotted quantity" or "proportion".
