1. What is the Normality Index?

The Normality Index is a statistical measure that compares observed values to expected values under a normal distribution. It helps determine how much an observed count deviates from what would be expected.

2. How Does the Calculator Work?

The calculator uses the Normality Index formula:

Where:

• \( \text{Observed} \) — The actual count observed in your data
• \( \text{Expected} \) — The count expected under normal distribution

Explanation: The index measures how many standard deviations the observed count is from the expected count. Positive values indicate higher than expected, negative values indicate lower than expected.

3. Importance of Normality Index

Details: This index is useful in statistical quality control, biological studies, and any field where comparing observed frequencies to expected frequencies is important for assessing normality or detecting anomalies.

4. Using the Calculator

Tips: Enter both observed and expected counts as positive numbers. The expected value must be greater than zero.

5. Frequently Asked Questions (FAQ)

Q1: What does a Normality Index of 0 mean?
A: An index of 0 means the observed count exactly matches the expected count.

Q2: How do I interpret positive vs. negative values?
A: Positive values indicate the observed is higher than expected, negative values indicate it's lower than expected.

Q3: What range of values is considered "normal"?
A: Typically, values between -2 and +2 are considered within normal range, but this depends on your specific application.

Q4: Can I use this for small sample sizes?
A: The index becomes less reliable with very small expected counts (typically <5).

Q5: How is this different from a z-score?
A: This is essentially a z-score for count data, measuring how many standard deviations an observation is from the expected value.