Excerpt from Alternative Tests for the Selection of Model VariablesAbout the PublisherForgotten Books publishes hundreds of thousands of rare and classic books.This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works. This text has been digitally restored from a historical edition. Some errors may persist, however we consider it worth publishing due to the work's historical value.The digital edition of all books may be viewed on our website before purchase.
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Excerpt from Alternative Tests for the Selection of Model Variables
One of the most difficult and subtle tasks confronting the mathematical model-builder is the selection of appropriate variables and functional relationships for his model. In specifying each equation, the modeler faces two distinct problems. First, he must posit a priori hypotheses about the variables or factors which he believes are impor tant causes of change in the dependent variable of that equation. Sec ond, once such hypotheses have been advanced, the modeler must have some means of testing whether or not, given the available empirical information, those variables which a priori reasoning has led him to consider should be included in the model. Based on the results of such testing, the modeler may be led to reject certain variables as being relatively unimportant, and may thereby begin to refine his initial causal hypotheses.
About the Publisher
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This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.
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Librería: Forgotten Books, London, Reino Unido
Paperback. Condición: New. Print on Demand. This book explores the difficulties of evaluating cause and effect using simple statistical techniques. The author provides a detailed critique of traditional methods, demonstrating how they can lead to erroneous conclusions. The author then presents a more comprehensive approach to causal modeling, one that takes into account the complex feedback loops that exist in real-world systems. This groundbreaking approach, which the author terms "whole-model testing," provides researchers with a more accurate and reliable way to determine the true impact of individual variables. The insights offered in this book have the potential to revolutionize the way we conduct scientific research and make decisions in a wide range of fields. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book. print-on-demand item. Nº de ref. del artículo: 9781332248919_0
Cantidad disponible: Más de 20 disponibles
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: LW-9781332248919
Cantidad disponible: 15 disponibles
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: LW-9781332248919
Cantidad disponible: 15 disponibles