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**Table of Content**

The effect size calculator calculates the strength of correlation and relationship between two variables on the numeric scale. The practical effect of a variable is identified by the effect size of various variables of the sample.

**“Effect is the measure of the numeric value or the effect size between the two samples on the basis of standard deviation and sample size”**

For instance, Cohen’s d effect size can be used to identify the difference between the height of men and women. The larger the effect size the greater the difference between the height of men and women. The estimated effect size of variables describes their correlation.

You can calculate the effect size of Cohen’s method. It calculates the difference between two populations and is divided by the standard deviation of the population.

Consider two samples of height for men and women and these samples have equal standard deviation of 3. Each sample has a size of 10 and the average height of men is 6 feet and women is 5 feet.

\(bar x_1 = 6 ; bar x_2 = 5\)

\(n_1 = 10 ; n_2 = 10\)

\(S_1 = 3 ; S_2 = 3\)

\(S^2 = \dfrac{(n_1 – 1)S_1^2 + (n_2 – 1)S_2^2}{n_1 + n_2 – 2}\)

\(S^2 = \dfrac{(10 – 1)(3)^2 + (10 – 1)(3)^2}{10 + 10 – 2}\)

\(S^2 = \sqrt{9}\)

S = 3

Now effect size:

\(d = \dfrac{|{{\bar x}}_1 – {{\bar x}}_2|}{S}\)

\(d = \dfrac{|6 – 5|}{3}\)

\(d = \dfrac{1}{3}\)

\(d = 0.3333\)

In the above example, Cohen’s d-effect size of two samples of equal standard deviation is used. You can calculate the effect size of unequal standard deviation by the effect size calculator.

The various formulas used in calculating effect size are as follows:

\(S^2 = \dfrac{(n_1 – 1)S_1^2 + (n_2 – 1)S_2^2}{n_1 + n_2 – 2}\)

\(d = \dfrac{|{{\bar x}}_1 – {{\bar x}}_2|}{S}\)

\(S^2 = \dfrac{S_1^2 + S_2^2}{2}\)

\(d = \dfrac{|{{\bar x}}_1 – {{\bar x}}_2|}{S}\)

\(d = \dfrac{|{{\bar x}} – μ_0|}{S}\)

\(h = 2(arcsin(\sqrt{p_1}) – arcsin(\sqrt{p_2}))\)

\(φ = \sqrt{\dfrac{X^2}{n}}\)

\(V = \sqrt{\dfrac{X^2}{n_1 * Min(R-1 , C-1)}}\)

\(f^2 = \dfrac{R^2}{1 – R^2}\)

\(R^2 = \dfrac{f^2}{1 + f^2}\)

You need to calculate the effect size before starting your research and after completing the research. A Cohen’s d calculator is a simple way to apply the standard deviation of the samples in the study.

Let’s estimate effect size by the Campbell effect size calculator which is very easy to use and yields instant outcomes.

**Input:**

- Choose the effect size type
- Enter the required parameters in each respective field
- Hit the calculate button

**Output:**

- The effect size of each type

From the source of scribbr.com: Effect Size, How to Calculate Effect Size?

From the source of wallstreetmojo.com:Corelation and Effect Size, How to Find Effect Size?