Question 1

What factors influence the required sample size?

Accepted Answer

Sample size depends on the desired confidence level, margin of error, population size, and expected effect size (MDE). Larger effects require smaller samples, while smaller effects require larger samples to detect.

Question 2

What is the difference between confidence level and margin of error?

Accepted Answer

Confidence level (typically 95%) indicates how confident you are in your results. Margin of error is the range of uncertainty around your estimate. A higher confidence level or smaller margin of error requires larger samples.

Question 3

In what proportion should groups be divided for A/B tests?

Accepted Answer

Use a conservative approach - an equal split into two groups in 50/50 proportions.

Question 4

What if I have a limited number of study participants?

Accepted Answer

If the population is limited, use a finite population correction and try to maximize coverage. In the case of very small samples, use non-parametric analysis methods and consider reduced statistical power.

Question 5

How does the choice of Minimum Detectable Effect (MDE) affect the practical utility of the study?

Accepted Answer

If you choose too small an MDE, a huge sample will be required, which may be impractical. If you choose too large an MDE, you might miss small but important effects. The optimal MDE should reflect the business or research value of the effect.

Question 6

What is statistical power and why is it important in sample size calculation?

Accepted Answer

Statistical power is the probability of detecting a real effect (if it exists) and avoiding a Type II error (a false negative). Higher power (typically 80% or more) requires a larger sample size to ensure you don't miss a significant result.

Question 7

What is the impact of variability (standard deviation) on sample size?

Accepted Answer

The greater the variability in the population data (standard deviation), the larger the sample size needed to achieve the same precision. This is because greater variability makes it harder to obtain an accurate estimate of the population mean.

Question 8

When should I use sample size calculation for comparative studies (e.g., A/B tests)?

Accepted Answer

For comparative studies, you need a sample size calculation that considers the Minimum Detectable Effect (the smallest difference you deem important) and statistical power to ensure your experiment is capable of detecting that difference.

A/B testing Calculator: Sample Size

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A/B testing Calculator: Sample Size

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