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Effect Size Calculator

Four ways in — two groups, a t, an F, or a correlation r — and conversions between d, r, η² and the odds ratio. A p-value says whether an effect is there; these say how big it is, which is the number a reader actually needs.

Sample size calculatorFind the survey sample size needed for a population, confidence level and margin of error.ANOVA Calculator (One-Way)Full one-way ANOVA table — SS, df, MS, F and p — plus η², ω² and Cohen's f, because a significant F on its own tells you nothing about how large the difference is. The equal-variance assumption is stated, not buried.Average Deviation Calculator (mean absolute deviation)The average absolute deviation from the mean AND from the median — the median is the point that minimises it, which is worth seeing. Every |x − centre| is listed, and the standard deviation sits beside it for contrast: squaring makes SD react hard to a single outlier while the average deviation barely moves. The outlier preset is built to show exactly that.Bayes Theorem CalculatorCompute the posterior probability P(A|B) with the probability tree, the natural-frequency restatement and the base-rate lesson that makes a 99 % accurate test right only 16.7 % of the time.Beta Distribution CalculatorCompute beta-distribution probabilities on [0,1] from shape parameters α and β via the regularized incomplete beta function.Binomial Probability CalculatorGet P(X=k) and every cumulative form at once for up to 1000 trials, with the mean, variance, mode and a chart of the whole distribution.Binomial Theorem Expansion CalculatorExpand (a + b)ⁿ up to n = 50 with exact coefficients, the Pascal triangle row, the general term and any single term you ask for — negative b handled sign by sign.Central Limit Theorem CalculatorProbabilities for a sample mean from the population mean, standard deviation and sample size, with the standard error and the z-scores shown.

Open Effect Size Calculator and you get an answer straight away, with no account to create. Its place is under Statistics & probability; Sample size calculator and ANOVA Calculator (One-Way) answer the questions closest to this one.

How to use it

  1. Open the tool — no signup or install needed.
  2. Enter your input or adjust the available options.
  3. Get your result instantly, then copy or download it.

Frequently asked questions

What is Effect Size Calculator?

Four ways in — two groups, a t, an F, or a correlation r — and conversions between d, r, η² and the odds ratio. A p-value says whether an effect is there; these say how big it is, which is the number a reader actually needs.

When would I actually use this?

Summarising a dataset before drawing conclusions from it, checking whether a difference between two groups is real, and putting an interval around an estimate.

What is the most common mistake?

Reading a p-value as the probability that the hypothesis is wrong. It is the probability of seeing data at least this extreme if the null were true — a different statement, and a much weaker one.

How is Effect Size Calculator different from Sample size calculator?

They sit next to each other but answer different questions: Sample size calculator is the one to open when you need it to find the survey sample size needed for a population, confidence level and margin of error. Pick whichever matches what you're starting from — both are free.

Is there a tool for the next step?

ANOVA Calculator (One-Way) is the closest one after this: Full one-way ANOVA table — SS, df, MS, F and p — plus η², ω² and Cohen's f, because a significant F on its own tells you nothing about how large the difference is. The equal-variance assumption is stated, not buried.

What else is worth having open alongside it?

Average Deviation Calculator (mean absolute deviation) and Bayes Theorem Calculator — they come up in the same task often enough to be worth a second tab.

Where do the figures come from?

Distributions and test statistics are computed from their standard definitions, not from a lookup table, so results carry more digits than a printed table would. The assumptions each test makes are stated with it.

Further reading

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