P-Value Calculator · Practical guide
P Value from Z Score Calculator
Turn any z-statistic into one- and two-tailed p-values, instantly.
At a glance
The Short Answer
For a Z-statistic, the one-tailed p-value is the area of the standard normal curve beyond |z|, and the two-tailed value doubles it. The most quoted example: z = 1.96 gives a two-tailed p of 0.0500 — the conventional significance threshold.
Interactive tool
P-Value Calculator
Enter your own values, then compare the result with the examples below.
P-Value Results
Common Z-Scores and Their P-Values
| Z-Score | One-Tailed p | Two-Tailed p |
|---|---|---|
| 1.282 | 0.100 | 0.200 |
| 1.645 | 0.050 | 0.100 |
| 1.960 | 0.025 | 0.050 |
| 2.326 | 0.010 | 0.020 |
| 2.576 | 0.005 | 0.010 |
How to Read the Result
The p-value is the probability of seeing a Z-statistic this extreme if the null hypothesis were true. A two-tailed p of 0.050 for z = 1.96 means results this far from zero would occur by chance 5% of the time — just significant at α = 0.05. Enter any z-score above, positive or negative; the calculator uses the absolute value.
No Degrees of Freedom Needed
Unlike T and Chi-square tests, the standard normal distribution is fully defined on its own — no degrees of freedom required. That makes Z-based p-values the fastest to compute, and the ones behind most large-sample tests of means and proportions.
Frequently Asked Questions
What p-value does z = 1.645 give?
A one-tailed p of 0.050 and a two-tailed p of 0.100. It is the classic cutoff for a one-tailed test at alpha = 0.05.
Should I use the one-tailed or two-tailed result?
Use whichever matches the hypothesis you set before collecting data. Two-tailed is the default in most research because it detects effects in either direction.
What if my z-score is negative?
Enter it as-is. The p-value depends on the absolute value of z, so -1.96 and +1.96 produce identical results.
When is a Z-test appropriate instead of a T-test?
Z-tests fit large samples or situations where the population standard deviation is known. With small samples and an estimated standard deviation, the T-test is the right choice.