ANOVA Test


Analysis of Variance (ANOVA):
Equality of Normal Populations


Versión en Español
Colección de JavaScript Estadísticos en los E.E.U.U.
Sitio Espejo para América Latina


This site is a part of the JavaScript E-labs learning objects for decision making. Other JavaScript in this series are categorized under different areas of applications in the MENU section on this page.

Professor Hossein Arsham   


The following JavaScript tests a claim on simultaneous equality of means of three normal populations, having almost the same variances, based on three sets of random observations. If you need ANOVA for more than three populations then use ANOVA for Condensed Data Sets JavaScript.

Enter up-to-40 sample data from the first population, the second population, and the third population in the following three tables, respectively. Blank entry boxes are not included in the calculations but zeros are.

In entering your data to move from cell to cell in the data-matrix use the Tab key not arrow or enter keys.

The aim is to test the claim that:

m1 = m2 = m3

Formaly,

H0: The populations' means are almost the same.
Ha: At least one population's mean differs quite significantly from the others.

To edit your data, including add/change/delete, you do not have to click on the "clear" button, and re-enter your data all over again. You may simply add a number to any blank cell, change a number to another in the same cell, or delete a number from a cell. After editing, then click the "calculate" button.

For extensive edit or to use the JavaScript for a new set of data, then use the "clear" button.






Mean1 Variance1
Mean2 Variance2
Mean3 Variance3
Variation Between
Variation Within
F-Statistic
P-Value
Conclusion




For Technical Details, Back to:
Statistical Thinking for Decision Making


Kindly email your comments to:
Professor Hossein Arsham


Comparación de Tres Medias: Análisis de Varianza (ANOVA)
Nota para los usuarios de habla hispana:
El siguiente JavaScript prueba la propuesta para la igualdad de medias de tres poblaciones normales basada en un conjunto de observaciones aleatorias.
Introduzca hasta 40 datos muestrales de la primera, segunda y tercera población respectivamente en las tres tablas siguientes. Los espacios en blanco no son asumidos como ceros ni incluidos en los cálculos, pero los números cero si se incluyen.
Mientras entre sus datos en la matriz, muévase de celda a celda usando la tecla Tab, no use la flecha o la tecla de entrada.
El objetivo es probar la proposición de que:
mu1 = mu2 = mu3
Formalmente,
H0: Las medias poblacionales son casi la misma.
Ha: Al menos una media poblacional difiere significativamente de las otras.
Para editar sus datos (incluyendo agregar, cambiar o borrar), usted no tiene que presionar el botón Clear (Limpiar) para vaciar la matriz e introducir los datos de nuevo. Usted puede simplemente agregar, cambiar o borrar   números en cualquier celda. Después de editar, presione el botón Calculate (Calcular).
Para una edición de datos mas extensiva, o para usar la matriz para incluir nuevos datos utilice el botón Clear (Limpiar).
Los resultados que usted obtendrá de esta matriz son:
Mean 1 = Media 1
Variance 1 = Varianza 1
Mean 2 = Media 2
Variance 2 = Varianza 2 Mean 3 = Media 3
Variance 3 = Varianza 3
Variation Between = Variación Entre (intervalo)
Variation Within = Variación Dentro de
F- Statistic = F Estadístico
P – Value = Valor P
Conclusion = Conclusión:
Very strong evidence against the null hypothesis = Evidencia bastante fuerte en contra de la hipótesis nula
Moderate evidence against the null hypothesis = Evidencia moderada en contra de la hipótesis nula
Suggestive evidence against the null hypothesis = Evidencia subjetiva en contra de la hipótesis nula
Little or no real evidences against the null hypothesis = Poca o no evidencia real en contra de la hipótesis nula
Strong evidence against the null hypothesis = Evidencia fuerte en contra de la hipótesis nula

Para Detalles Técnicos y Aplicaciones, Vuelta a:
Razonamiento Estadístico para la Toma de Decisiones Gerenciales


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Kindly e-mail me your comments, suggestions, and concerns. Thank you.

Professor Hossein Arsham   


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