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Cohens D Calculator

Calculate summary metrics, mean, median, mode, variance, standard deviation, quartiles, and correlation for cohens d.

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Input Data Set

Enter comma-separated numbers for statistical analysis.

Calculated Metric Value

21.71 mean
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Statistical Rule

For symmetric distributions, Mean = Median. For skewed distributions, the median is more robust against extreme outliers than the mean.

Calculation Methodology & Details

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Formula

Sample Mean: x̄ = Σx / n Sample Variance: s² = Σ(x - x̄)² / (n - 1) Standard Deviation: s = √s²

Applies standard descriptive statistics definitions, Tukey 1.5×IQR outlier boundaries, and Pearson moment equations.

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Important Disclaimer

Calculations assume unweighted sample measurements unless weighted frequencies or grouped interval classes are specified.

How to Calculate Step-by-Step

Follow these steps to complete the calculation:

1

Step 1

Enter dataset values separated by commas, spaces, or line breaks.

2

Step 2

Select sample (n-1) vs population (N) variance mode or target percentile rank.

3

Step 3

View 5-number summary (Min, Q1, Median, Q3, Max), standard deviation, skewness, or outlier flags.

Detailed Insights & Expert Guide

ℹ️ About this Calculation

The Cohens D Calculator computes summary location statistics (mean, median, mode), dispersion metrics (range, IQR, variance, standard deviation), correlation (Pearson, Spearman), and shape moments (skewness, kurtosis).

Variable Glossary

Input

Data Points (x_i)

Numerical measurements collected in the sample observation vector.

Parameter

Degree of Freedom (n - 1)

Bessel's correction factor for unbiased sample variance estimation.

FAQ

How is an outlier detected using the 1.5×IQR Rule?
An observation is flagged as an outlier if it falls below the Lower Fence (Q1 - 1.5 × IQR) or above the Upper Fence (Q3 + 1.5 × IQR), where IQR = Q3 - Q1.
What is the 5-Number Summary?
The 5-Number Summary consists of five key order statistics: Minimum, First Quartile (25th percentile Q1), Median (50th percentile Q2), Third Quartile (75th percentile Q3), and Maximum.
What does the Coefficient of Variation (CV) measure?
Coefficient of Variation (CV = s / x̄ × 100%) measures relative dispersion, allowing comparison of variability between datasets measured in completely different units.