Calculadora de Tamanho do Efeito (Cohen)
Calcule o tamanho do efeito usando o d de Cohen para pesquisas educacionais.
Average of all pairwise item correlations
Cronbach's Alpha
0.896
Cronbach's Alpha vs Number of Test Items
Formula
## How Cronbach's Alpha Works Cronbach's Alpha estimates reliability based on the number of items and their average correlation. Higher alpha means the items consistently measure the same construct. ### Standardized Alpha Formula **Alpha = (k x r_avg) / (1 + (k - 1) x r_avg)** Where k is the number of items and r_avg is the average inter-item correlation. ### Interpretation - 0.90+: Excellent reliability - 0.80-0.89: Good reliability - 0.70-0.79: Acceptable reliability - Below 0.70: Questionable to poor
Exemplo Resolvido
A 20-item survey has an average inter-item correlation of 0.30.
- 01Numerator: 20 x 0.30 = 6.0
- 02Denominator: 1 + (20 - 1) x 0.30 = 1 + 5.7 = 6.7
- 03Alpha = 6.0 / 6.7 = 0.896
- 04Interpretation: Good reliability (0.80-0.89)
Perguntas Frequentes
Can Alpha be too high?
Yes. Alpha above 0.95 may indicate redundant items that could be removed to shorten the test without losing reliability.
How many items do I need for good reliability?
More items generally increase alpha. With moderate inter-item correlations (0.2-0.4), 15-20 items usually achieve alpha above 0.80.
What is the difference between Alpha and test-retest reliability?
Alpha measures internal consistency (one administration). Test-retest measures stability over time (two administrations).