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The number of observations or units included in a sample for analysis.
DESCRIPTION
Sample size determines statistical power, precision, and reliability of estimates. Larger samples reduce variance and improve confidence intervals, subject to diminishing returns. Proper sizing depends on effect size, variability, significance level, and desired power. In A/B tests, sample calculations ensure valid conclusions and ethical exposure. Underpowered studies risk false negatives; oversized samples waste resources.
ALTERNATIVE DEFINITIONS
NIST/SEMATECH e-Handbook
The sample size is the number of observations in the sample.
Concise, textbook definition in a trusted handbook.
Penn State STAT 500
Sample size refers to the number of units or observations included in a sample.
Course material contextualizing sample sizing for studies.
UCLA Statistical Consulting
Sample size is the count of observations in a dataset used to estimate population parameters.
Practical framing for applied statistics.
RELATED TERMS
Power Analysis Confidence Interval Standard Error Population Effect Size Central Limit Theorem A/B Testing Variance
COMPETING TERMS
KNOWLEDGE AREAS
Mathematics Data Science Testing & Validation
TARGET AUDIENCE
Data Scientist Data Analyst AI Product Manager Business Analyst Information Analyst
EXTERNAL SOURCES
- Wikipedia - Sample size
- NIST - Handbook definition and context
- Penn State - Course lesson on sample size
- UCLA - Consulting guide on sample size
TOP QUESTIONS
Why does Sample Size matter in A/B testing?
It determines statistical power and reliability; too small risks missing true effects, too large wastes time and resources.
Category: Relevancy
How do you calculate Sample Size?
Use expected effect size, variance, significance level, and desired power; closed-form formulas or tools like G*Power help.
Category: Techniques
What is a common mistake in Sample Size planning?
Ignoring variance and effect size, or peeking mid-experiment without correction, biases results.
Category: Mistakes
What happens if Sample Size is too small?
Estimates are noisy, confidence intervals widen, and false negatives increase.
Category: Risk
Is bigger always better for Sample Size?
Beyond a point, gains diminish; balance costs, ethics, and timing against precision needs.
Category: Opinion
How does Sample Size relate to Standard Error?
Standard error shrinks roughly with the square root of sample size, improving precision.
Category: Relationship
What is a competing concept to Sample Size?
A Census measures the entire population, eliminating sampling error but often impractical.
Category: Alternatives
Does Sample Size affect p-values?
Yes; large samples can make tiny effects statistically significant—interpret with effect size and confidence intervals.
Category: Misunderstanding
Where should beginners learn Sample Size basics?
Start with NIST’s handbook, university course notes, and hands-on examples using calculators.
Category: GettingStarted