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.
- Why is Sample Size Determination Important?
- How Does Low Power Affect Study Results?
- Factors Influencing the Power of Statistical Tests
- 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
- Determination of Power & Sample Size in Practice
- Graphical Tools for Power and Sample Size Analysis
- Other Considerations: Post-Hoc Power Calculations, Simulation Methods, Ethical Considerations
- Available Computational Resources: Java Applets, Statistical Software
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
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
Recommended Duration: 1 day(s)