Multiple Linear Regressions

Multiple Linear Regressions Analysis

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   

Multiple linear regressions are extensions of simple linear regression with more than one dependent variables. This JavaScript provides multiple linear regressions up to four independent variables .

Using the data table, enter up-to-16 sample ordered-data sets (X1, Y), (X1, X2, Y), (X1, X2, X3, Y) or (X1, X2, X3, X4, Y) depending on the intended application, and then click the Calculate Calculate button located on the first box where the fitted model will appear.

Obviously, sample size is going to limit how many predictors you want to use in the multiple regressions.

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

The Fitted Model is :

  X1 X2 X3 X4 Y Predicted
Y values
Diagnostic Tools for Data Transformation Decisions
R-Square F-Statistic
Mean Variance
The first half
The second half
The first-half
The second half
First order serial-correlation Second order serial-correlation
Durbin-Watson statistic Mean absolute errors
Normality Condition:
ith Residual:


For Technical Details, Back to:
Business Statistics

Kindly email your comments to:
Professor Hossein Arsham

Análisis de Regresión Lineal Múltiple
Nota para los usuarios de habla hispana:
Regresiones lineales múltiples son extensiones de la regresión lineal simple con mas de una variable dependiente. Este JavaScript proporciona regresiones lineales múltiples hasta con tres variables independientes.
Introduzca hasta 16 conjunto de pares de datos tales como (X1, Y), (X1, X2, Y), (X1, X2, X3, Y), ó (X1, X2, X3, X4, Y), dependiendo de las aplicaciones, y luego presione el botón Calculate (Calcular.)
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.
Los resultados que usted obtendrá de esta matriz son:
The Fitted Model is = El Modelo Ajustado es...
Predicted Y values = Valores Y estimados
Diagnostic Tools for Data Transformation Decisions = Herramientas Diagnósticas para Decisiones sobre Transformaciones de Datos
R- square = R al cuadrado
F- statistic = Estadístico F
Mean = Media
Variance = Varianza
Mean the fisrst half = Media de la Primera Mitad
Mean the second half = Media de la Segunda Mitad
Variance the fisrst half = Varianza de la Primera Mitad
Variance the second half = Varianza de la Segunda Mitad
Second order serial- correlation = Correlación de Serie de Segundo Grado
First order serial- correlation = Correlación de Serie de Primer Grado
Durbin- Watson Statistic = Estadístico Durbin- Watson
Mean Absolute Error = Error Absoluto de la Media
Normality Condition = Condición de Normalidad
Ith Residual = Iésimo Residuo

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


Decision Tools in Economics & Finance

Probabilistic Modeling


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

Professor Hossein Arsham   

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Dr Arsham's Home Page

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