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Calculate power & sample size for one-sample, two-sample and k-sample experiments. Advanced power and sample size calculator online: calculate sample size for a single group, or for differences between two groups (more than two groups supported for binomial data).
The power calculator computes the test power based on the sample size and draw an accurate power analysis chart. Larger sample size increases the statistical power. The test power is the probability to reject the null assumption, H 0, when it is not correct. Power = 1- β.
Calculator to determine the minimum number of subjects to enroll in a study for adequate power.
Free, Online, Easy-to-Use Power and Sample Size Calculators. no java applets, plugins, registration, or downloads ... just free. Go Straight to the Calculators ».
Calculator to determine the post-hoc power of an existing study.
Choose which calculation you desire, enter the relevant population values for mu1 (mean of population 1), mu2 (mean of population 2), and sigma (common standard deviation) and, if calculating power, a sample size (assumed the same for each sample).
You can use this calculator to estimate: The sample size a planned study will need to detect an effect size at a given power level; The statistical power a planned study will have based on the expected sample and effect sizes 1; The smallest effect size a planned study can detect for a given power level and sample size
Interactive calculator for illustrating power of a statistical hypothesis test. alpha $\alpha$ : Difference in means $\delta_a$ : Sample size in each group $n$ :
Choose which calculation you desire, enter the relevant values for mu0 (known value), mu1 (mean of the population to be sampled), and sigma (standard deviation of the sampled population) and, if calculating power, a sample size.
Calculate sample size of a certain power for your experiments. Baseline Conversion Rate (%) Minimum Detectable Effect (%) Hypothesis. One-sided Test (Recommended) Used to determine if the test variation is better than the control (Recommended) Two-sided Test.