Q‑Score Calculator for Data Arrays

Q‑Score Calculator for Data Arrays

Enter two data arrays and the standard deviation. The Q‑Score is computed as: $$ Q = \frac{\text{Mean}_1 – \text{Mean}_2}{\text{SD} \times \sqrt{\frac{1}{n_1} + \frac{1}{n_2}}}. $$

* Ensure the data arrays contain numeric values and that SD > 0.

Step 1: Enter Parameters

e.g., 65,70,75,80,85

e.g., 60,65,70,75,80

Enter the pooled or within‑group standard deviation (e.g., 10)

How It Works

The calculator extracts the means and sample sizes from the data arrays:

  • \(\text{Mean}_1\) and \(n_1\) are computed from Data Array 1
  • \(\text{Mean}_2\) and \(n_2\) are computed from Data Array 2

Then, the Q‑Score is calculated as: $$ Q = \frac{\text{Mean}_1 – \text{Mean}_2}{\text{SD} \times \sqrt{\frac{1}{n_1} + \frac{1}{n_2}}}. $$

Formula: \( Q = \frac{\text{Mean}_1 – \text{Mean}_2}{\text{SD} \times \sqrt{\frac{1}{n_1} + \frac{1}{n_2}}} \)