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  4. /P-Value Calculator (T-Score)

P-Value Calculator (T-Score)

Last updated: March 28, 2026

Calculator

Results

Two-Tailed P-Value

0.329114

One-Tailed P-Value (Either Side)

0.164557

|T| Used in Calculation

1

Results

Two-Tailed P-Value

0.329114

One-Tailed P-Value (Either Side)

0.164557

|T| Used in Calculation

1

This P-Value Calculator converts a t-score into a p-value for quick hypothesis-test interpretation. Enter your t-score and degrees of freedom (df) to get both a two-tailed p-value and a one-tailed p-value (either side).

Note: This version uses a fast approximation designed to stay close to the Student’s t-distribution (especially as df grows). For extremely small df, exact t-distribution calculators may differ slightly.

Visual Analysis

How It Works

For Student’s t-tests, p-values come from the t-distribution, which depends on df. Because the distribution is symmetric, we work with |t| and compute tail probabilities.

  • One-tailed (either side): p = 1 − F(|t|)
  • Two-tailed: p = 2 × (1 − F(|t|))

This calculator uses a df-based transformation of |t| into an adjusted z-like value and then converts it into tail probability using a standard normal CDF approximation.

Understanding Your Results

Smaller p-values indicate that observing a t-score at least as extreme as yours would be less likely under the null hypothesis. Many U.S. use cases compare p-values to 0.05, but context and effect size still matter.

Worked Examples

Example: t = 1, df = 10

Inputs

t1
df10

Results

t abs used1
one tailed p0.170675
two tailed p0.341349

A t-score of 1 is usually not extreme. Two-tailed p should be well above 0.05.

Example: t = 2.5, df = 20

Inputs

t2.5
df20

Results

t abs used2.5
one tailed p0.010841
two tailed p0.021682

A stronger t-score. Two-tailed p is typically around 0.02.

Negative t-score: t = -1.5, df = 5

Inputs

t-1.5
df5

Results

t abs used1.5
one tailed p0.09896
two tailed p0.197921

Using |t| means negative and positive t-scores of the same magnitude give the same p-values.

Frequently Asked Questions

Use a t-score when the population standard deviation is unknown and sample sizes are smaller. The t-distribution accounts for extra uncertainty through degrees of freedom.

Degrees of freedom often relate to sample size (for example, df = n − 1 in a one-sample t-test). The exact df depends on the test setup.

Two-tailed tests check for differences in both directions (higher or lower than the reference). It’s common when you care about any deviation.

The distribution is symmetric around 0. Using |t| measures extremeness regardless of sign and keeps the p-value logic consistent.

It will be very close for moderate-to-large df. For very small df, exact t-distribution CDF values can differ slightly. If you need exact matching, the platform should support a true t-distribution CDF function.

Sources & Methodology

Student’s t-distribution and p-value interpretation in hypothesis testing.
R

Roboculator Team

The Roboculator Team explains calculations, planning tools, and practical formulas in clear language for real-life situations.

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