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Related Concept Videos

Sample Size Calculation01:19

Sample Size Calculation

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Knowledge of the sample size is the first requirement to conduct random sampling or an experiment. The sample size is the total number of units, observations, or groups (in some cases) used to get the data to estimate a population parameter. As the name suggests, the sample size is that of the sample drawn from the population and differs from the population size.
The sample size for the given experiment or sampling effort is fundamental to any study design. Sample size decides the number of...
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Systematic Sampling Method01:17

Systematic Sampling Method

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
Systematic sampling is one of the simplest methods...
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Sampling Methods: Overview01:06

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A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling. 
In analytical chemistry, the choice of...
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One-Way ANOVA: Unequal Sample Sizes01:15

One-Way ANOVA: Unequal Sample Sizes

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One-way ANOVA can be performed on three or more samples of unequal sizes. However, calculations get complicated when sample sizes are not always the same. So, while performing ANOVA with unequal samples size, the following equation is used:
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One-Way ANOVA: Equal Sample Sizes01:15

One-Way ANOVA: Equal Sample Sizes

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One-Way ANOVA can be performed on three or more samples with equal or unequal sample sizes. When one-way ANOVA is performed on two datasets with samples of equal sizes, it can be easily observed that the computed F statistic is highly sensitive to the sample mean.
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
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Contaminants and Errors01:16

Contaminants and Errors

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Effective sample preparation is crucial for accurate and reliable laboratory analysis. During this process, two significant sources of error can arise: concentration bias from improper sample splitting and contamination caused by methods used to reduce particle size, such as grinding or homogenization. Identifying and minimizing these potential errors is crucial to ensuring the validity of the analysis.
Another key consideration is determining the appropriate number of samples required to...
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5. Determining the size of sample for rigorous conclusions.

A Indrayan1

  • 1Department of Clinical Research, Max Healthcare, New Delhi, India.

Journal of Postgraduate Medicine
|November 20, 2025
PubMed
Summary

Determining the correct sample size is crucial for rigorous health and medical research. This study offers a general method for calculating sample size for statistical inferences, considering factors like margin of error and clinical importance.

Keywords:
Confidence intervalslarge samplemedical significancepowerreliability of the estimatessmall sample

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Area of Science:

  • Health and Medical Research
  • Biostatistics
  • Empirical Study Design

Background:

  • Sample size determination is a critical concern in health and medicine research.
  • Adequate sample size ensures the rigor and validity of research conclusions.
  • Standard methods differ for population parameter estimation versus hypothesis testing.

Purpose of the Study:

  • To compile essential considerations for determining adequate sample size in empirical research.
  • To provide a general method for computing sample size for two types of statistical inferences.
  • To enhance researchers' understanding of sample size calculation intricacies.

Main Methods:

  • Compilation of factors influencing sample size, including inter-subject variability and study design.
  • Development of a general method for sample size computation for parameter estimation and hypothesis testing.
  • Presentation of sources and tools for sample size calculation.

Main Results:

  • A unified approach to sample size calculation is presented, integrating various factors.
  • The study offers a general method applicable to different statistical inference types.
  • Key ingredients and complexities in sample size determination are highlighted.

Conclusions:

  • Accurate sample size calculation is vital for achieving rigorous research outcomes.
  • The provided methods and considerations aid researchers and statisticians in determining appropriate sample sizes.
  • Understanding sample size intricacies improves the reliability of health and medical studies.