Work out type i and type ii error instantly with clear inputs, formula shown and shareable results.
A Type I error rejects a true null hypothesis and occurs with probability α. A Type II error fails to reject a false null and occurs with probability β; power is 1 − β and rises with both the effect size and the sample size.
Power
power = 1 − β = P(reject | the alternative is true)
Beta
β = Φ(z_crit − δ) − Φ(−z_crit − δ)
The critical z is 1.96, so β ≈ 0.4840 and the power is about 51.6% — a coin flip.
Increase the sample size, reduce measurement noise, or accept a larger α. There is always a trade-off with the Type I rate.