Use this calculator to compute a P value from a Z, t, F, r, or chi-square value.
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Normal, Student's T, Chi-Square and F Statistical Tables from SOCR (UCLA)
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This page allows you to generate random integers in a given interval.
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Randomly assign subjects to groups; Simulate data by generating random numbers; Randomly select a subset of subjects.
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RANDOM.ORG offers true random numbers to anyone on the Internet. The randomness comes from atmospheric noise, which for many purposes is better than the pseudo-random number algorithms typically used in computer programs.
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This screen computes the sample size required to detect a difference between two proportions.
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Online calculation for sample size, power or the minimal detectable difference for parallel studies, crossover studies, or studies to find associations between variables, where the dependent variable is Success or Failure, a Quantitative Measurement, or a time to an event such as a survival time.
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Randomizatio.com is an online resource to help for block randomization in clinical trials.
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QMinim is an online free minimisation service for minimising subjects to different arms of a clinical trial.
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This page from RV Lenth provides graphical interfaces for studying the power of one or more tests. They include sliders (convertible to number-entry fields) for varying parameters, and a simple provision for graphing one variable against another.
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This web site allows you to generate random numbers from a Gaussian distribution under a given mean and standard deviation.
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Research Randomizer is a closed-source, clinical randomization web service, It can be used for random sampling, random assignment to treatment groups, and block randomization. This randomization service has an excellent tutorial with five sample randomization scenarios for random sampling, random assignment, random block assignment, generating random numbers in a specified range, and random ordering of a set of items,
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The calculator (from University college, London) helps in calculating the probability that a results associated to asignificant P value, after doing a single unbiased experiment, is a false positive. False positive risk (FPR) is defined here as the probability that a result which is significant at a specified P value, is a false positive result.
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These utilities can be used to calculate required sample sizes to estimate a population mean or proportion, to detect significant differences between two means or two proportions or to estimate a true herd-level prevalence.
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These utilities can be used to calculate confidence limits and summarise a variety of categorical or continuous data.
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