Regression Analysis

1743 words - 7 pages

ANÃLISIS DE REGRESIÃ"N LINEAL Ãndices Bursátiles de EUA y México Eduardo J. Paxson Páez Universidad Anáhuac Maestría en Alta Dirección Administración de Operaciones I Prof. Francisco Reyes 19 de septiembre de 2001.INDICE I. INTRODUCCIÃ"N II. CASO DE ESTUDIO III. ESTADÃSTICAS BASICAS IV. REGRESIÃ"N LINEAL. MODELO LINEAL SIMPLE.V. AJUSTE DEL MODELO LINEAL DE ORDEN 1 VI. AJUSTE DE MODELO LINEAL DE ORDEN 2 VII. AJUSTE DEL MODELO CUBICO VIII. AJUSTE DE MODELO POLINOMIAL DE SEXTO ORDEN IX. CONCLUSIONES X. BIBLIOGRAFÃA I. INTRODUCCIÃ"N En todo sistema en el cual los valores de variables cambian, es de interés examinar los efectos que algunas variables puedan tener sobre otras. Incluso se puede llegar a descubrir una relación funcional entre ellas. Esto es, sin embargo, la excepción al estudiar procesos físicos. Muy a menudo existe una relación funcional descrita por una función matemática simple, como sería un polinomio, que contiene las variables pertinentes y se aproxima a la función verdadera. Al analizar dicha "función aproximada" podremos aprender más acerca de la verdadera relación entre las variables y de los efectos independientes y conjuntos producidos con el cambio de ciertas variables importantes.Aún cuando no existe una relación física tangible entre variables, puede ser de interés relacionarlas a través de una ecuación matemática. Aunque físicamente la relación matemática carecerá de sentido, dicha ecuación puede ser muy valiosa para efectos de predicción de los valores de alguna(s) variable(s) dado el conocimiento de otras.Para efectos de mi estudio, describiré y utilizaré el método de "mínimos cuadrados" para examinar los datos y sacar de ellos conclusiones significativas sobre relaciones de dependencia que pudieran existir. Este método de análisis es conocido como Análisis de Regresión. Particularmente, ajustaré la forma más sencilla de regresión por mínimos cuadrados, ajustando "la mejor" línea recta a los datos X y Y. Cabe destacar que este caso de ajuste de una recta se puede generalizar a casos en donde un mayor número de variables estén involucradas.Los propósitos de la regresión los puedo resumir en los siguientes puntos: · Describir los datos · Resumir los datos · Comprender / representar relaciones o...

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