Statistik & Wahrscheinlichkeit
Sofort, privat und kostenlos
Inverse Normal Distribution Calculator.
Calculate this statistic instantly with validated formulas.
Werte eingeben
Ergebnisse werden während der Eingabe aktualisiert.
Use Cases
Statistical Hypothesis Testing
Find critical z-values for confidence intervals or hypothesis tests. For a given significance level (e.g., 0.05), the inverse normal gives the z-score that defines the rejection region.
Example: For a two-tailed test with alpha = 0.05, enter 0.975 to get z = 1.96.
Data Normalization and Outlier Detection
Convert probabilities to z-scores to standardize data or identify outliers. This helps in comparing values from different normal distributions.
Example: If a value corresponds to the 90th percentile, enter 0.9 to get z ≈ 1.28.
Frequently Asked Questions
- What is the inverse normal distribution?
- The inverse normal distribution, also known as the inverse Gaussian or normal quantile function, returns the z-score corresponding to a given cumulative probability under the standard normal distribution. For example, a probability of 0.975 gives a z-score of approximately 1.96.
- How do I use this calculator?
- Enter one or more probabilities (values between 0 and 1) separated by commas or spaces. The calculator will compute the corresponding z-scores using the standard normal distribution. Ensure each value is a valid probability; otherwise, the result may be undefined.
- What is the range of input values?
- The input values must be probabilities between 0 and 1 (exclusive). Values outside this range are not valid for the inverse normal distribution. For example, 0.5 is valid, but 1.5 is not.
Tips & Common Mistakes
Tips
- Ensure your input values are between 0 and 1. If you have percentages, convert them to decimals (e.g., 95% becomes 0.95).
- For a two-tailed test, use the probability 1 - (alpha/2) to get the critical z-score. For example, alpha = 0.05 gives 0.975.
- You can enter multiple probabilities at once to get a list of z-scores, which is useful for comparing different percentiles.
- Remember that the inverse normal distribution assumes a standard normal distribution (mean = 0, standard deviation = 1).
Common Mistakes to Avoid
- Entering values outside the 0-1 range, such as 1.5 or -0.2, which are not valid probabilities.
- Confusing the inverse normal with the normal CDF: the inverse normal takes a probability and returns a z-score, not the other way around.
- Using percentages without converting to decimals, e.g., entering 95 instead of 0.95.
Last updated: August 13, 2026