What are the common mistakes in sample size calculation?
An example of an AI chatbot conversation about common mistakes in sample size calculation.
What are the common mistakes in sample size calculation?
Common mistakes include not considering effect size, ignoring population variability, and using outdated formulas.
Can you explain why effect size is important?
Effect size helps determine the magnitude of a difference, which is crucial for calculating an adequate sample size.
What happens if I underestimate the sample size?
Underestimating sample size can lead to insufficient power, increasing the risk of Type II errors and unreliable results.
Are there any tools to help with sample size calculation?
Yes, there are several online calculators and software like G*Power and R that can assist with sample size determination.
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