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Regression for Economics, Second Edition
Regression for Economics, Second Edition
Knygos.lt klubas Knygos.lt nariams
22,25 €
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31,79 €
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Regression analysis can be used to establish causal relationships between factors and the response variable. However, in order to be able to do so, economic theory must be used to provide the causal relationship and then regression analysis is applied to verify the validity of the theory. Regression analysis is the most commonly used analytical tool and can be understood without complex mathematics. This book simplifies and demystifies regression analysis. All the examples are from economics an…

Regression for Economics, Second Edition (el. knyga) (skaityta knyga) | knygos.lt

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Regression analysis can be used to establish causal relationships between factors and the response variable. However, in order to be able to do so, economic theory must be used to provide the causal relationship and then regression analysis is applied to verify the validity of the theory. Regression analysis is the most commonly used analytical tool and can be understood without complex mathematics. This book simplifies and demystifies regression analysis. All the examples are from economics and in almost all the cases, real data is used to show the application of the method. By limiting the use of mathematical symbols, the author enables a logical reader to learn regression, without shortchanging the subject. The book is targeted to all business students and executives who need to understand the concept of regression for practical and professional purposes.

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Regression analysis can be used to establish causal relationships between factors and the response variable. However, in order to be able to do so, economic theory must be used to provide the causal relationship and then regression analysis is applied to verify the validity of the theory. Regression analysis is the most commonly used analytical tool and can be understood without complex mathematics. This book simplifies and demystifies regression analysis. All the examples are from economics and in almost all the cases, real data is used to show the application of the method. By limiting the use of mathematical symbols, the author enables a logical reader to learn regression, without shortchanging the subject. The book is targeted to all business students and executives who need to understand the concept of regression for practical and professional purposes.

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