1. What is the T-Test P Value?

The p-value in a t-test represents the probability of obtaining test results at least as extreme as the observed results, assuming the null hypothesis is true. It helps determine the statistical significance of your findings.

2. How Does the Calculator Work?

The calculator uses the t-distribution formula:

Where:

• \( P \) — Two-tailed p-value
• \( t \) — Calculated t-statistic from your data
• \( df \) — Degrees of freedom
• \( T.CDF \) — Cumulative distribution function of the t-distribution

Explanation: The formula calculates the probability of observing a t-value as extreme as, or more extreme than, the calculated value under the null hypothesis.

3. Importance of P Value Calculation

Details: P-values are crucial in hypothesis testing as they help researchers determine whether to reject the null hypothesis. A small p-value (typically ≤ 0.05) indicates strong evidence against the null hypothesis.

4. Using the Calculator

Tips: Enter the t-value (can be positive or negative) and degrees of freedom. The calculator will return the two-tailed p-value. For one-tailed tests, divide the result by 2.

5. Frequently Asked Questions (FAQ)

Q1: What is a statistically significant p-value?
A: Typically, p-values less than or equal to 0.05 are considered statistically significant, though this threshold can vary by field.

Q2: What's the difference between one-tailed and two-tailed tests?
A: One-tailed tests look for an effect in one direction only, while two-tailed tests consider both directions. This calculator provides two-tailed p-values.

Q3: How do I calculate degrees of freedom?
A: For a one-sample t-test, df = n-1. For independent two-sample t-test, df = n₁ + n₂ - 2.

Q4: What if my p-value is exactly 0.05?
A: This is at the conventional threshold for significance. Interpretation depends on your field's standards and the context of your research.

Q5: Can p-values be greater than 1?
A: No, p-values range from 0 to 1, representing probabilities.