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| Concept |
Description |
Impact on A/B Testing |
| Estimating |
The process of making an educated guess about a population parameter based on a sample statistic. |
Estimating the effect size of an A/B test is crucial in determining whether the results are statistically significant and meaningful. A larger sample size generally leads to more accurate estimates. |
| Sampling |
The process of selecting a subset of individuals from a population to represent the entire population. |
The sample size and selection method can impact the validity and reliability of A/B test results. A larger and more representative sample is generally preferred. |
| Variability |
The degree to which data points in a sample or population differ from each other. |
High variability can make it more difficult to detect significant differences between A/B test groups. It is important to control for variability as much as possible through randomization and other experimental design techniques. |
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