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Related Concept Videos

Sample Size Calculation01:19

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 Errors01:16

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...
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Overview of Biostatistics in Health Sciences01:19

Overview of Biostatistics in Health Sciences

Biostatistics involves the application of statistical techniques to scientific research in health-related fields, including biology and public health. These techniques are essential for designing studies, collecting data, and analyzing it to draw meaningful conclusions. Given the complexity of biological processes, particularly in studies involving human subjects, biostatistical methods are crucial for effectively organizing and interpreting data that might otherwise obscure underlying patterns...
Biostatistics: Overview01:20

Biostatistics: Overview

Biostatistics plays a crucial role in understanding and analyzing data in healthcare and biology. Biostatisticians conduct experiments, gather evidence, and draw meaningful conclusions using statistical methods and techniques. Different variables form the foundation of biostatistical analysis, allowing researchers to understand and interpret data effectively. These variables are classified into different types, each serving a specific purpose in statistical analysis.
Discrete variables are...
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...

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Related Experiment Video

Updated: Jul 8, 2026

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow
08:58

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow

Published on: October 17, 2025

Essential tips on sample size calculation and biostatistics.

Daniel Y T Fong1, Pui Hing Chau1, K F Lam2

  • 1School of Nursing, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, the Hong Kong Special Administrative Region of China.

Best Practice & Research. Clinical Obstetrics & Gynaecology
|July 6, 2026
PubMed
Summary
This summary is machine-generated.

This guide offers practical advice for clinical researchers on sample size calculation and biostatistical analysis. It emphasizes clear objectives and appropriate methods for robust study design and reliable results.

Keywords:
BiostatisticsGenerative artificial intelligenceSample size

Related Experiment Videos

Last Updated: Jul 8, 2026

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow
08:58

Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow

Published on: October 17, 2025

Area of Science:

  • Clinical Research Methodology
  • Biostatistics

Background:

  • Clinical research relies heavily on sample size calculation and biostatistical analysis.
  • Many clinician-researchers face challenges in applying appropriate methods for these crucial aspects.

Purpose of the Study:

  • To provide non-statisticians with practical, principle-based guidance on sample size determination and analysis planning.
  • To demystify complex statistical concepts for clinician-researchers.

Main Methods:

  • Guidance on establishing clear study objectives as the foundation.
  • Key considerations for sample size determination, including study type, analysis plan, effect size, and multiplicity.
  • Core principles for biostatistical analysis, covering software, regression, missing data, and error control.

Main Results:

  • Clear study objectives are essential for both sample size determination and analysis planning.
  • Practical considerations for sample size calculation include distinguishing study types and defining meaningful effect sizes.
  • Fundamental biostatistical analysis principles involve using appropriate software, handling data correctly, and controlling errors.

Conclusions:

  • Effective sample size calculation and biostatistical analysis are achievable for non-statisticians with clear objectives and adherence to core principles.
  • This guidance supports the design of more rigorous and reliable clinical research studies.