Regression for economics:
Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
New York, N.Y.
Business Expert Press
2012
|
| Edition: | 1st ed |
| Series: | 2012 digital library
Economics and finance collection |
| Subjects: | |
| Online Access: | BSB01 |
| Item Description: | Part of: 2012 digital library. - Mode of access: World Wide Web. - System requirements: Adobe Acrobat reader Includes bibliographical references (p. 135-136) and index The concept of regression was introduced by Sir Francis Galton, but R.A. Fisher provided the statistical theory and application for it for the first time. The 20th century witnessed the spread of regression analysis into every scientific branch. Regression analysis is the most commonly used statistical method in the world. It is used in economics and many other fields. Although few would characterize this technique as simple, regression is in fact both simple and elegant. The complexity that many attribute to regression analysis is often a reflection of their lack of familiarity with the language of mathematics. But regression analysis can be understood even without a mastery of sophisticated mathematical concepts. This book provides the foundation of the regression analysis. All the examples are from economics, and in almost all the examples the real data is used to show the applications of the method |
| Physical Description: | 1 Online-Ressource (XIX, 140 S.) |
| ISBN: | 9781606494066 9781606494059 |
Staff View
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| 500 | |a The concept of regression was introduced by Sir Francis Galton, but R.A. Fisher provided the statistical theory and application for it for the first time. The 20th century witnessed the spread of regression analysis into every scientific branch. Regression analysis is the most commonly used statistical method in the world. It is used in economics and many other fields. Although few would characterize this technique as simple, regression is in fact both simple and elegant. The complexity that many attribute to regression analysis is often a reflection of their lack of familiarity with the language of mathematics. But regression analysis can be understood even without a mastery of sophisticated mathematical concepts. This book provides the foundation of the regression analysis. All the examples are from economics, and in almost all the examples the real data is used to show the applications of the method | ||
| 505 | 0 | |a Foreword -- Acknowledgments -- Introduction -- 1. The concept of regression -- 2. The method of least squares -- 3. Simple linear regression in Excel -- 4. Multiple regression -- 5. Goodness of fit -- 6. Regression coefficients -- 7. Causality: correlation is not causality -- 8. Qualitative variables in regression -- 9. Pitfalls of regression analysis -- Appendix -- Glossary -- Notes -- References -- Index | |
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| author_facet | Naghshpour, Shahdad |
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| contents | Foreword -- Acknowledgments -- Introduction -- 1. The concept of regression -- 2. The method of least squares -- 3. Simple linear regression in Excel -- 4. Multiple regression -- 5. Goodness of fit -- 6. Regression coefficients -- 7. Causality: correlation is not causality -- 8. Qualitative variables in regression -- 9. Pitfalls of regression analysis -- Appendix -- Glossary -- Notes -- References -- Index |
| ctrlnum | (ZDB-30-PQE)ebr10617487 (OCoLC)814468732 (DE-599)BVBBV040784481 |
| dewey-full | 519.536 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.536 |
| dewey-search | 519.536 |
| dewey-sort | 3519.536 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| edition | 1st ed |
| format | Electronic eBook |
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| id | DE-604.BV040784481 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T00:33:46Z |
| institution | BVB |
| isbn | 9781606494066 9781606494059 |
| language | English |
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| physical | 1 Online-Ressource (XIX, 140 S.) |
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| publishDate | 2012 |
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| publisher | Business Expert Press |
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| series2 | 2012 digital library Economics and finance collection |
| spelling | Naghshpour, Shahdad Verfasser aut Regression for economics Shahdad Naghshpour 1st ed New York, N.Y. Business Expert Press 2012 1 Online-Ressource (XIX, 140 S.) txt rdacontent c rdamedia cr rdacarrier 2012 digital library Economics and finance collection Part of: 2012 digital library. - Mode of access: World Wide Web. - System requirements: Adobe Acrobat reader Includes bibliographical references (p. 135-136) and index The concept of regression was introduced by Sir Francis Galton, but R.A. Fisher provided the statistical theory and application for it for the first time. The 20th century witnessed the spread of regression analysis into every scientific branch. Regression analysis is the most commonly used statistical method in the world. It is used in economics and many other fields. Although few would characterize this technique as simple, regression is in fact both simple and elegant. The complexity that many attribute to regression analysis is often a reflection of their lack of familiarity with the language of mathematics. But regression analysis can be understood even without a mastery of sophisticated mathematical concepts. This book provides the foundation of the regression analysis. All the examples are from economics, and in almost all the examples the real data is used to show the applications of the method Foreword -- Acknowledgments -- Introduction -- 1. The concept of regression -- 2. The method of least squares -- 3. Simple linear regression in Excel -- 4. Multiple regression -- 5. Goodness of fit -- 6. Regression coefficients -- 7. Causality: correlation is not causality -- 8. Qualitative variables in regression -- 9. Pitfalls of regression analysis -- Appendix -- Glossary -- Notes -- References -- Index Wirtschaft Economics / Statistical methods Regression analysis Regressionsanalyse (DE-588)4129903-6 gnd rswk-swf Regressionsanalyse (DE-588)4129903-6 s 1\p DE-604 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Naghshpour, Shahdad Regression for economics Foreword -- Acknowledgments -- Introduction -- 1. The concept of regression -- 2. The method of least squares -- 3. Simple linear regression in Excel -- 4. Multiple regression -- 5. Goodness of fit -- 6. Regression coefficients -- 7. Causality: correlation is not causality -- 8. Qualitative variables in regression -- 9. Pitfalls of regression analysis -- Appendix -- Glossary -- Notes -- References -- Index Wirtschaft Economics / Statistical methods Regression analysis Regressionsanalyse (DE-588)4129903-6 gnd |
| subject_GND | (DE-588)4129903-6 |
| title | Regression for economics |
| title_auth | Regression for economics |
| title_exact_search | Regression for economics |
| title_full | Regression for economics Shahdad Naghshpour |
| title_fullStr | Regression for economics Shahdad Naghshpour |
| title_full_unstemmed | Regression for economics Shahdad Naghshpour |
| title_short | Regression for economics |
| title_sort | regression for economics |
| topic | Wirtschaft Economics / Statistical methods Regression analysis Regressionsanalyse (DE-588)4129903-6 gnd |
| topic_facet | Wirtschaft Economics / Statistical methods Regression analysis Regressionsanalyse |
| work_keys_str_mv | AT naghshpourshahdad regressionforeconomics |