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
- 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
- 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)