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Free P-Value Calculator — Convert Z-Scores to Statistical Significance

Enter your Z-score or test statistic and instantly know whether your research results are statistically significant — no tables, no formulas.

Result

0.0500

p-value

Z = 1.96 · TWO-TAILED

90% confidence · α 0.1Significant
95% confidence · α 0.05Significant
99% confidence · α 0.01Not significant

About this tool

A p-value is the cornerstone of statistical hypothesis testing — it tells you whether your research findings are likely to be real or merely the product of random chance. But converting a Z-score or test statistic into a p-value requires statistical tables or complex formulas that slow your analysis. Our free P-Value Calculator does it instantly: enter your Z-score and select your test type, and you’ll see your p-value and a clear significance verdict in seconds.

P-values appear across survey research, A/B testing, academic studies, clinical trials, and any experiment where you’re comparing two groups or testing a hypothesis. A p-value below your significance threshold — commonly 0.05 for 95% confidence, or 0.01 for 99% confidence — means your finding is statistically significant and you can reject the null hypothesis with appropriate confidence. A p-value above your threshold means you need more data or a larger observable effect before drawing conclusions.

This calculator supports both one-tailed and two-tailed tests, making it suitable for a wide range of research designs. Use it to validate survey findings, confirm A/B test results, support academic research, or check the statistical rigor of any experiment before publishing results or making decisions based on them.

Key benefits
Convert any Z-score to a p-value instantly — no statistical tables required
Supports both one-tailed and two-tailed hypothesis tests
Get a plain-English significance verdict alongside the raw p-value
Works for survey research, A/B testing, academic studies, and any hypothesis test
Completely free — no sign-up, no credit card, no limits
Pairs seamlessly with the A/B Testing Calculator and Sample Size Calculator
How it works
1

Enter your Z-score

Input the Z-score or test statistic from your analysis. This is typically the output from a hypothesis test comparing two groups or proportions.

2

Choose your test type

Select one-tailed (testing for a difference in one specific direction) or two-tailed (testing for any difference in either direction) based on your research hypothesis.

3

Get your p-value

See your p-value instantly, along with a clear verdict on whether your result is statistically significant at the 90%, 95%, and 99% confidence levels.

Quick answer

A p-value measures the probability that your research results occurred by random chance. To find a p-value from a Z-score, use a p-value calculator: enter your Z-score and select one-tailed or two-tailed based on your hypothesis. A Z-score of ±1.96 gives a p-value of 0.05 (95% confidence, two-tailed). A p-value below 0.05 is considered statistically significant in most research. Use a free p-value calculator to convert test statistics to significance levels instantly.

P-Value Calculator — FAQ

What is a p-value?+
A p-value is the probability of observing results as extreme as yours — or more extreme — if the null hypothesis were true. In plain language, it answers: “How likely is it that this result happened by chance?” A p-value of 0.05 means there’s a 5% chance the result is due to random variation. The lower the p-value, the stronger the evidence against the null hypothesis and in favor of a real effect.
What is a good p-value for survey research?+
In most business, social science, and market research, a p-value of 0.05 or lower is considered statistically significant — meaning less than a 5% probability that the result occurred by chance. For more rigorous research — medical studies, policy decisions, or high-stakes business commitments — use a threshold of 0.01. Never change your significance threshold after seeing your results, as this inflates the risk of false positives significantly.
What’s the difference between a one-tailed and two-tailed test?+
A two-tailed test checks whether there is a difference between your groups in either direction — your variant could be better or worse than your control. This is the appropriate default for most A/B tests and comparative surveys. A one-tailed test checks for a difference in only one specific direction — for example, testing whether a new feature specifically increases (not just changes) conversion rates. One-tailed tests are statistically more powerful but require a pre-specified directional hypothesis before data collection begins.
How is a Z-score related to a p-value?+
A Z-score measures how many standard deviations your observed result falls from what you’d expect under the null hypothesis. The further your Z-score from zero, the more unusual your result is — and the lower your p-value. A Z-score of ±1.96 corresponds to a p-value of 0.05 for a two-tailed test (95% confidence). A Z-score of ±2.576 corresponds to a p-value of 0.01 (99% confidence). Our calculator converts any Z-score to its exact corresponding p-value.
What should I do if my p-value is not significant?+
A non-significant p-value (above your threshold, usually 0.05) does not mean your hypothesis is wrong — it means you don’t yet have enough evidence to confirm it. Your options are: (1) increase your sample size to detect a smaller effect; (2) improve your measurement precision by refining your survey design; (3) reconsider whether the effect you’re looking for is large enough to matter practically; or (4) report the null result transparently — non-significant findings are scientifically valid and important to share.

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