1. What is a P Value in T Test?

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 statistical significance of your findings.

2. How Does the Calculator Work?

The calculator uses the t-distribution formula:

Where:

• \( p \) — P value (dimensionless)
• \( t \) — T-statistic from your test
• \( df \) — Degrees of freedom

Explanation: The t-distribution is used instead of normal distribution when sample sizes are small and population standard deviation is unknown.

3. Importance of P Value Calculation

Details: P values help researchers determine whether to reject the null hypothesis. Typically, p < 0.05 is considered statistically significant.

4. Using the Calculator

Tips: Enter the t-statistic from your test and the degrees of freedom. The calculator will compute the two-tailed p-value.

5. Frequently Asked Questions (FAQ)

Q1: What's the difference between one-tailed and two-tailed tests?
A: One-tailed tests check for an effect in one direction only, while two-tailed tests check in both directions. This calculator provides two-tailed p-values.

Q2: How do I determine degrees of freedom?
A: For a one-sample t-test, df = n-1 (sample size minus 1). For independent two-sample t-test, df = n1 + n2 - 2.

Q3: What is a good t-statistic value?
A: There's no "good" absolute value - it depends on your sample size and effect size. Larger absolute t-values (positive or negative) typically indicate stronger evidence against the null.

Q4: When should I use a t-test?
A: Use when comparing means between two groups, especially with small sample sizes (n < 30) and when population standard deviation is unknown.

Q5: What if my p-value is exactly 0.05?
A: This is at the conventional threshold for significance. Consider the context, effect size, and whether you should adjust for multiple comparisons.