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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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Contaminants and Errors01:16

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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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One-Way ANOVA: Unequal Sample Sizes01:15

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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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Distributions to Estimate Population Parameter01:26

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The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...
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Estimating Population Mean with Unknown Standard Deviation01:22

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In practice, we rarely know the population standard deviation. In the past, when the sample size was large, this did not present a problem to statisticians. They used the sample standard deviation s as an estimate for σ and proceeded as before to calculate a confidence interval with close enough results. However, statisticians ran into problems when the sample size was small. A small sample size caused inaccuracies in the confidence interval.
William S. Gosset (1876–1937) of the...
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Sampling Distribution01:12

Sampling Distribution

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Given simple random samples of size n from a given population with a measured characteristic such as mean, proportion, or standard deviation for each sample, the probability distribution of all the measured characteristics is called a sampling distribution. How much the statistic varies from one sample to another is known as the sampling variability of a statistic. You typically measure the sampling variability of a statistic by its standard error. The standard error of the mean is an example...
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Related Experiment Video

Updated: Dec 25, 2025

Problem-Solving Before Instruction PS-I: A Protocol for Assessment and Intervention in Students with Different Abilities
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Tips for troublesome sample-size calculation.

Junyong In1, Hyun Kang2, Jong Hae Kim3

  • 1Department of Anesthesiology and Pain Medicine, Dongguk University Ilsan Hospital, Goyang, Korea.

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|April 2, 2020
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Summary

Determining the correct sample size is crucial for research validity and impact. This review covers key factors for accurate sample size calculation, including endpoints, statistics, and error rates, to ensure robust scientific findings.

Keywords:
BiostatisticsEffect sizeIndependent t-testP valuePowerSample size

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Area of Science:

  • Biostatistics
  • Clinical Research Methodology
  • Scientific Research Design

Background:

  • Sample size determination is critical for research credibility and statistical power.
  • Balancing statistical significance with financial and medical feasibility is a key challenge in study design.

Purpose of the Study:

  • To review essential factors influencing sample size calculations in research.
  • To provide guidance on selecting appropriate sample sizes for scientific studies.

Main Methods:

  • Review of fundamental elements for sample size calculation.
  • Explanation of primary endpoints, statistical analysis, type I error, power, and effect size.
  • Inclusion of methods for adjusting sample size based on anticipated dropout rates.

Main Results:

  • Identified key statistical and practical considerations for sample size determination.
  • Demonstrated appropriate and inappropriate examples of sample size reporting in published literature.
  • Provided a framework for calculating adjusted sample sizes accounting for participant attrition.

Conclusions:

  • Accurate sample size calculation is fundamental for ensuring research power and validity.
  • Understanding the interplay of endpoints, statistics, and error rates is essential for appropriate sample size selection.
  • Consideration of dropout rates is necessary for robust sample size planning in clinical research.