P-value Calculator
Calculator to compute p-value from Z-score or Z-score from p-value for a normal distribution.
How to Use the P-value Calculator
Enter test statistic and distribution context (z, t, chi-square, etc.) to estimate p-value for hypothesis testing.
Null-Model Compatibility
P-value quantifies extremeness relative to null-distribution expectations.
Interpretation Guardrails
Avoid treating p-value as direct truth probability for hypotheses.
Tail Specification
One-sided vs two-sided framing materially changes results.
Evidence Context
Effect size and confidence intervals should accompany p-values.
Methodological Integrity
Pre-registered analysis and assumption checks improve reliability.
Frequently Asked Questions
What is p-value?+
Probability of seeing data this extreme if null hypothesis were true.
Is p-value probability null is true?+
No, it is conditional on null, not direct probability of null truth.
What does small p-value indicate?+
Data appears less compatible with null under test assumptions.
Does p < 0.05 prove practical importance?+
No, statistical significance is not the same as practical effect size.
Can one-tailed vs two-tailed change p?+
Yes, test direction specification affects p-value computation.
Does larger sample always reduce p-value?+
Larger samples can detect smaller effects, often lowering p-values.
Should confidence intervals be reported too?+
Yes, intervals provide effect-size uncertainty context.
Can p-hacking distort conclusions?+
Yes, selective analysis inflates false-positive risk.
Is p-value alone enough for decisions?+
No, combine with design quality, assumptions, and effect size.
Can assumptions invalidate p-value?+
Yes, violated model assumptions can make p-values misleading.
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