P-value Calculator
Calculate the P-value from a Z-score for statistical analysis.
P-value Calculator
Please provide any one value below to compute the p-value from z-score, or vice versa for a normal distribution.
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Understand Statistical Significance with a P-Value Calculator
Our P-Value Calculator helps you determine the statistical significance of your data by calculating the p-value from a Z-score.
What is a P-Value Calculator?
A p-value calculator is a statistical tool that converts a test statistic (like a Z-score) into a p-value. The p-value is a critical concept in hypothesis testing, as it helps you decide whether to accept or reject your null hypothesis based on the strength of your evidence. This tool is essential for students, researchers, and analysts in various fields.
How It Works: The Z-Score to P-Value Conversion
The calculator uses the cumulative distribution function (CDF) of the standard normal distribution to find the probability associated with a given Z-score. This corresponds to the area under the bell curve, which is the p-value.
Frequently Asked Questions
What is a p-value?
The p-value, or probability value, is a measure in statistics that helps determine the significance of your results in relation to a null hypothesis. It tells you the probability of observing your data, or something more extreme, if the null hypothesis were true.
How do you interpret a p-value?
A small p-value (typically ≤ 0.05) indicates strong evidence against the null hypothesis, so you reject the null hypothesis. A large p-value (> 0.05) indicates weak evidence against the null hypothesis, so you fail to reject the null hypothesis. It does not prove the null hypothesis is true, only that you don't have enough evidence to reject it.
What is the difference between a one-tailed and a two-tailed test?
A one-tailed test checks for a relationship in one direction (e.g., if a new drug is *better* than an old one). A two-tailed test checks for a relationship in either direction (e.g., if a new drug is simply *different* from an old one, either better or worse).
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