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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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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.
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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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Passive filters are utilized to shape the frequency spectrum of signals across a diverse array of applications. These filters, using only passive elements like resistors (R), inductors (L), and capacitors (C), are capable of selectively allowing or blocking certain frequency ranges without the need for external power sources.
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Active filters are electronic circuits that use operational amplifiers (op-amps), resistors, and capacitors to filter out unwanted frequency components from a signal. A first-order low-pass active filter is designed to pass signals with a frequency lower than a certain cutoff frequency and attenuate frequencies higher than that cutoff frequency. The transfer function for a first-order low-pass active filter is:
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Cell sizes vary widely among and within organisms. Bacterial cells range between 1-10 micrometers (μm)and are considerably smaller than most eukaryotic cells. The smallest bacteria are 0.1 μm in diameter—about a thousand times smaller than eukaryotic cells, which typically range from 10-100 μm.
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Related Experiment Video

Updated: Feb 14, 2026

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
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Tool for filtering PubMed search results by sample size.

Carlos Baladrón1, Alejandro Santos-Lozano2, Javier M Aguiar3

  • 1i+HeALTH Research Group, Miguel de Cervantes European University, Higher Polytechnic School, Department of Technical Teachings, Valladolid, Spain.

Journal of the American Medical Informatics Association : JAMIA
|February 7, 2018
PubMed
Summary

A new tool estimates sample sizes for clinical trials from PubMed abstracts, aiding researchers in advanced searches. This tool accurately classifies trial sample sizes, improving literature review efficiency.

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Area of Science:

  • Biomedical Informatics
  • Clinical Research
  • Bibliometrics

Background:

  • PubMed is a primary resource for scientific literature searches.
  • Sample size is a critical factor in evaluating clinical trial reports.
  • PubMed lacks a direct filter for sample size, hindering specific searches.

Purpose of the Study:

  • To develop a tool for filtering PubMed search results by reported sample size.
  • To enhance the ability of researchers to find clinical trials based on sample size.

Main Methods:

  • A search engine was created to query PubMed and retrieve article abstracts.
  • Syntactical and machine learning methods were employed to estimate sample sizes.
  • The tool's accuracy was validated against a manually annotated database of 750 clinical trials.

Main Results:

  • The tool accurately estimates sample size for 70% of abstracts.
  • It correctly classifies 85% of abstracts into sample size quartiles.
  • The tool demonstrates utility for advanced PubMed searches.

Conclusions:

  • The developed tool is effective for filtering PubMed clinical trial searches by sample size.
  • It supports researchers in identifying trials relevant to meta-analyses and experimental therapy support.