Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Sample Size Calculation

Sample Size Calculation

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...

Contaminants and Errors

Contaminants and Errors

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...

Margin of Error

Margin of Error

The margin of error is also called the maximum error of an estimate. The margin of error is the maximum possible or expected difference between the observed sample parameter value and the actual population parameter value. For proportion, it is the maximum difference between the value of sample proportion obtained from the data and the true value of population proportion. As the true value of the population parameter is not known, the margin of error is calculated using the sample statistic.

Sampling Distribution

Sampling Distribution

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...

Sample Proportion and Population Proportion

Sample Proportion and Population Proportion

Collecting samples or responses from an entire population takes significant time and effort, so a researcher collects responses from only a sample of that population. Suppose a study needs to collect information about a specific mobile application. After sample collection, the researcher analyzes the data and discovers that most individuals in the sample use that specific mobile application. The sample proportion measures the number of individuals in a sample who either use or don't use the...

One-Way ANOVA: Unequal Sample Sizes

One-Way ANOVA: Unequal Sample Sizes

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:

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Risk, Predictors, and Outcomes of Acute Kidney Injury in Patients Admitted to Intensive Care Units in Egypt.

Scientific reports·2017

Same author

Long-Term Progression of Coronary Artery Calcification Is Independent of Classical Risk Factors, C-Reactive Protein, and Parathyroid Hormone in Renal Transplant Patients.

Cardiorenal medicine·2017

Same author

Obesity and kidney disease: Hidden consequences of the epidemic.

African journal of primary health care & family medicine·2017

Same author

Validation of echocardiographic criteria for the clinical diagnosis of heart failure in chronic kidney disease.

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association·2017

Same author

Optimizing hypertension management in renal transplantation: a call to action.

Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association·2017

Same author

Optimizing hypertension management in renal transplantation: a call to action.

Journal of hypertension·2017

Search research articles

Related Experiment Video

Updated: Jun 4, 2026

Modeling the Size Spectrum for Macroinvertebrates and Fishes in Stream Ecosystems

Modeling the Size Spectrum for Macroinvertebrates and Fishes in Stream Ecosystems

Published on: July 30, 2019

Sample size calculations.

Marlies Noordzij¹, Friedo W Dekker, Carmine Zoccali

¹ERA-EDTA Registry, Department of Medical Informatics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands. m.noordzij@amc.uva.nl

Nephron. Clinical Practice

|February 5, 2011

Summary

This summary is machine-generated.

Calculating the correct sample size is crucial for research success. This guide explains basic principles and demonstrates sample size calculation for simple study designs to avoid wasting resources or missing significant findings.

More Related Videos

Automatic Image Processing to Determine the Community Size Structure of Riverine Macroinvertebrates

Automatic Image Processing to Determine the Community Size Structure of Riverine Macroinvertebrates

Published on: January 13, 2023

Related Experiment Videos

Last Updated: Jun 4, 2026

Modeling the Size Spectrum for Macroinvertebrates and Fishes in Stream Ecosystems

Modeling the Size Spectrum for Macroinvertebrates and Fishes in Stream Ecosystems

Published on: July 30, 2019

Automatic Image Processing to Determine the Community Size Structure of Riverine Macroinvertebrates

Automatic Image Processing to Determine the Community Size Structure of Riverine Macroinvertebrates

Published on: January 13, 2023

Area of Science:

Biostatistics
Clinical Research Methodology

Background:

Accurate sample size determination is essential for the validity and efficiency of research studies.
Insufficient sample size may lead to failure in detecting true effects, while excessive sample size results in wasted resources.
Existing statistical methods for sample size calculation can be complex and prone to errors due to sensitivity to parameter changes.

Purpose of the Study:

To elucidate the fundamental principles underlying sample size calculations in research.
To provide a clear demonstration of how to perform sample size calculations for straightforward study designs.
To aid researchers in selecting appropriate sample size methodologies and minimizing calculation errors.

Main Methods:

Explanation of core concepts in sample size determination.
Illustrative example of sample size calculation for a basic study design.
Discussion of common pitfalls and sources of error in sample size estimation.

Main Results:

Understanding the impact of parameter selection on sample size outcomes.
A practical framework for performing sample size calculations.
Guidance on choosing the correct sample size formula for specific research scenarios.

Conclusions:

Proper sample size calculation is vital for robust and cost-effective research.
This paper simplifies the understanding and application of sample size determination.
Researchers can improve study design by applying basic principles and demonstrated methods.