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Sample Size & Power Determination

Sample Size & Power Determination

Efficient experiments must be large enough to detect meaningful scientific differences and maximize the use of available resources. Learn about sample size and power calculations.

Course Details

Learning Objectives

Learning Objectives:

Upon completion of this module, participants will be able : 

  • To identify the parameters that influence power & sample size: 
  • To know how to carry out calculations and how to determine it in practice 
  • How to determine sample size for commonly used experimental designs
  • How to determine the power of statistical tests using user-friendly tools
  • How to use graphical tools as an aid in determining the balance between power and sample size


Target Audience

Target Audience:

This module is intended for all researchers and scientists who wish learn how to determine the power and the sample size of their experiments.



This module covers the principle underlying the determination of sample size to achieve a desired precision level and power for statistical tests. The course requirements are described as follows. Course participants must possess:

  • A working knowledge of descriptive statistics : mean, standard deviation, standard error, data distributions
  • A working knowledge of hypothesis testing:  H0, H1, test statistic, type I and II errors, and the confidence interval approach
  • Or, equivalently, the completion of the course: Fundamental Tools in Statistics for Research

Course Outline

Course Outline:
  • Why is Sample Size Determination Important?
  • How Does Low Power Affect Study Results?
  • Factors Influencing the Power of Statistical Tests
  • Determination of Power & Sample Size in Practice 
    • The Input Parameters: significance level, effect size, variability and power
    • How to Obtain an Estimate of Variability in Practice?
    • Determining Sample Size To Achieve a Desired Precision Level for a Mean or Proportion?
    • Determining Sample Size To Compare Two or More Means and Proportions?
    • Determining Sample Size for Other Advanced Statistical Tests: The Principle of Simulations
  • Graphical Tools for Power and Sample Size Analysis
  • Other Considerations: Post-Hoc Power Calculations, Simulation Methods, Ethical Considerations
  • Conclusion
  • Conventions
  • Available Computational Resources: Java Applets, Statistical Software

Practical Info

Practical Info:


Recommended Duration: 1 day

Course Materials:

  • Course notes on statistical techniques
  • Sample datasets

    Related Sessions

    • Variation is present in every experiment. Learn about DOE techniques to control variation, and to maximise data quality. Commonly used experimental designs are discussed as well as the statistical data analysis tools.

    • Learn about key biostatistical concepts and efficient tools for summarising and plotting data as well as outlier detection. Demystify the statistical testing approach used to make decision in the presence of uncertainty: p-values, power, and so on. 

    • This module covers key biostatistical concepts required to review and interpret findings published in the medical literature. Selected scientific publications are reviewed, discussed and criticised in terms of bias, uncertainty and scope. 

    • This session discusses key concepts in statistics. Classical and more recent exploratory data analysis techniques to efficiently summarise data and to detect outliers are presented. Statistical testing and decision-making in the presence of variation are also discussed.