Submitted by: Submitted by gared
Views: 304
Words: 3345
Pages: 14
Category: Business and Industry
Date Submitted: 02/27/2011 07:43 PM
Título del proyecto:
Aplicación del Análisis de Regresión Múltiple en el Análisis de la demanda de un producto.
Índice.
Resumen 3
Introducción 4
Marco Teórico 5
Historia del análisis de la regresión………………………………………………….5
Análisis de regresión…………………………………………………………………..5
El error estándar de la regresión múltiple…………………………………………6
El coeficiente de determinación múltiple…………………………………………..6
El análisis de correlación y regresión lineal entre variables cuantitativas………7
Regresión Lineal Múltiple……………………………………………………………..8
Selección de variables………………………………………………………………10
Interacción, confusión y colinealidad………………………………………………11
Metodología del Análisis de Regresión Lineal Múltiple………………………….12
Desarrollo del Proyecto 13
Resultados 13
Conclusiones 13
Bibliografía 17
Resumen
Finite mixture models have come to play a very prominent role in modeling data. The finite mixture model is predicated on the assumption that distinct latent groups exist in the population. The finite mixture model therefore is based on a categorical latent variable that distinguishes the different groups, the costs and organizational sophistication necessary to collect repeated measurements or longitudinal data.
Thus, what is needed is a generalization of the finite mixture’s discrete latent predictor to a continuous latent predictor. So we need to provide a validation of regression models from a practical point of view. In this text we try to show and learn the steps in the model-building process and to give an intuitive understanding of regression algorithms and the associated hypothesis tests and statistical intervals. A computer-based approach is used for calculations to minimize the number of equations and formulas used. The proposed approach is found to be quite flexible and performs either as well or better than traditional statistical methods. With these tools, we have an easy way to take the best choice, and minimize the risks.
Introducción
La venta de...