Calculadora de Tamaño de Muestra para Investigación Gratis
Determina el tamaño de muestra necesario para tu investigación educativa según poder y efecto.
1.645 = 90%, 1.96 = 95%, 2.576 = 99%
As a decimal, e.g. 0.05 for 5%
0.5 gives the largest (most conservative) sample
Leave large if unknown
Required Sample Size
370
Required Sample Size vs Z-Score for Confidence Level
Fórmula
## How to Calculate Sample Size The sample size formula balances precision against cost. A larger sample reduces the margin of error but requires more resources. ### Formula (Cochran's) **n_0 = Z^2 x p x (1 - p) / E^2** With finite population correction: **n = n_0 / (1 + (n_0 - 1) / N)** Where Z is the z-score for your confidence level, p is the expected proportion, E is margin of error, and N is population size. Using p = 0.5 gives the most conservative (largest) sample size when the true proportion is unknown.
Ejemplo Resuelto
A researcher needs 95% confidence (Z = 1.96), 5% margin of error, expected proportion 0.5, population 10,000.
- 01n_0 = 1.96^2 x 0.5 x 0.5 / 0.05^2 = 3.8416 x 0.25 / 0.0025 = 384.16
- 02Finite correction: 384.16 / (1 + 383.16 / 10000) = 384.16 / 1.0383 = 370
- 03Required sample size: 370
Preguntas Frecuentes
Why use 0.5 for proportion?
When you do not know the expected proportion, 0.5 maximizes the variance (p x (1-p)), giving the most conservative sample size.
What if my population is very large?
For very large populations, the finite correction has minimal effect and the sample size approaches the infinite-population formula.
How does confidence level affect sample size?
Higher confidence requires a larger sample. Going from 95% to 99% confidence increases sample size by about 75%.