⚙️ Test Type

🎛 Parameters

Sample size n 30 Effect size δ 0.5 Significance α 0.05 Std dev σ 1.0

t-statistic

—

p-value

—

Decision

—

Power (β)

—

Type I ✓

Type II ✗

Correct H₀

Correct H₁

ℹ️ About

A hypothesis test checks if data is consistent with the null hypothesis H₀. The p-value is the probability of observing a result at least as extreme if H₀ were true. If p < α, we reject H₀. Type I error = false rejection (α). Type II error = missed effect (β). Power = 1−β depends on n, δ, and σ.