The Resource Regression for economics, Shahdad Naghshpour
Regression for economics, Shahdad Naghshpour
Resource Information
The item Regression for economics, Shahdad Naghshpour represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Missouri University of Science & Technology Library.This item is available to borrow from 1 library branch.
Resource Information
The item Regression for economics, Shahdad Naghshpour represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in Missouri University of Science & Technology Library.
This item is available to borrow from 1 library branch.
 Summary
 The concept of regression was introduced by Legendre in 1805 and advanced by Gauss in 1809. The term was popularized after Galton's 1886 article. Contribution of R.A. Fisher in the early 20th century was instrumental to the spread of the method to every scientific branch. Regression analysis, used in economics and many other fields, is now the most commonly used statistical method. 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 the mastery of sophisticated mathematical concepts. This book provides the foundation of regression analysis in a way that is easy to comprehend. All the examples are from economics and in almost all the examples real data are used to show the application of the method
 Language
 eng
 Edition
 Second edition.
 Extent
 1 online resource (1 PDF (xix, 166 pages)).
 Note
 Title from PDF title page (viewed on May 12, 2016)
 Contents

 1. The concept of regression
 2. The method of least squares
 3. Simple linear regression using software packages
 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 of terms
 Notes
 References
 Index
 Isbn
 9781631574436
 Label
 Regression for economics
 Title
 Regression for economics
 Statement of responsibility
 Shahdad Naghshpour
 Subject

 Economics  Statistical methods
 Electronic books
 MATHEMATICS  Applied
 MATHEMATICS  Probability & Statistics  General
 Regression analysis
 Regression analysis
 Stata
 analysis
 causality
 ceteris paribus
 coefficient of determination
 control variables
 error
 goodness of fit
 inference
 misspecification
 model
 proxy variables
 regression
 spurious regression
 Economics  Statistical methods
 Language
 eng
 Summary
 The concept of regression was introduced by Legendre in 1805 and advanced by Gauss in 1809. The term was popularized after Galton's 1886 article. Contribution of R.A. Fisher in the early 20th century was instrumental to the spread of the method to every scientific branch. Regression analysis, used in economics and many other fields, is now the most commonly used statistical method. 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 the mastery of sophisticated mathematical concepts. This book provides the foundation of regression analysis in a way that is easy to comprehend. All the examples are from economics and in almost all the examples real data are used to show the application of the method
 Cataloging source
 NYBEP
 http://library.link/vocab/creatorName
 Naghshpour, Shahdad
 Dewey number
 519.536
 Index
 index present
 LC call number
 HB137
 LC item number
 .N247 2016
 Literary form
 non fiction
 Nature of contents

 dictionaries
 abstracts summaries
 bibliography
 Series statement
 Economics collection,
 http://library.link/vocab/subjectName

 Economics
 Regression analysis
 MATHEMATICS
 MATHEMATICS
 Economics
 Regression analysis
 Target audience
 specialized
 Label
 Regression for economics, Shahdad Naghshpour
 Note
 Title from PDF title page (viewed on May 12, 2016)
 Antecedent source
 unknown
 Bibliography note
 Includes bibliographical references (page 161) and index
 Carrier category
 online resource
 Carrier category code

 cr
 Carrier MARC source
 rdacarrier
 Color
 multicolored
 Content category
 text
 Content type code

 txt
 Content type MARC source
 rdacontent
 Contents
 1. The concept of regression  2. The method of least squares  3. Simple linear regression using software packages  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 of terms  Notes  References  Index
 Control code
 949862466
 Dimensions
 unknown
 Edition
 Second edition.
 Extent
 1 online resource (1 PDF (xix, 166 pages)).
 File format
 unknown
 Form of item
 online
 Isbn
 9781631574436
 Level of compression
 unknown
 Media category
 electronic
 Media MARC source
 isbdmedia
 Quality assurance targets
 not applicable
 Reformatting quality
 unknown
 Sound
 unknown sound
 Specific material designation
 remote
 System control number
 (OCoLC)949862466
 Label
 Regression for economics, Shahdad Naghshpour
 Note
 Title from PDF title page (viewed on May 12, 2016)
 Antecedent source
 unknown
 Bibliography note
 Includes bibliographical references (page 161) and index
 Carrier category
 online resource
 Carrier category code

 cr
 Carrier MARC source
 rdacarrier
 Color
 multicolored
 Content category
 text
 Content type code

 txt
 Content type MARC source
 rdacontent
 Contents
 1. The concept of regression  2. The method of least squares  3. Simple linear regression using software packages  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 of terms  Notes  References  Index
 Control code
 949862466
 Dimensions
 unknown
 Edition
 Second edition.
 Extent
 1 online resource (1 PDF (xix, 166 pages)).
 File format
 unknown
 Form of item
 online
 Isbn
 9781631574436
 Level of compression
 unknown
 Media category
 electronic
 Media MARC source
 isbdmedia
 Quality assurance targets
 not applicable
 Reformatting quality
 unknown
 Sound
 unknown sound
 Specific material designation
 remote
 System control number
 (OCoLC)949862466
Subject
 Economics  Statistical methods
 Electronic books
 MATHEMATICS  Applied
 MATHEMATICS  Probability & Statistics  General
 Regression analysis
 Regression analysis
 Stata
 analysis
 causality
 ceteris paribus
 coefficient of determination
 control variables
 error
 goodness of fit
 inference
 misspecification
 model
 proxy variables
 regression
 spurious regression
 Economics  Statistical methods
Genre
Member of
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<div class="citation" vocab="http://schema.org/"><i class="fa faexternallinksquare fafw"></i> Data from <span resource="http://link.library.mst.edu/portal/RegressionforeconomicsShahdad/WBu7m_6ESU/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.library.mst.edu/portal/RegressionforeconomicsShahdad/WBu7m_6ESU/">Regression for economics, Shahdad Naghshpour</a></span>  <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.library.mst.edu/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.library.mst.edu/">Missouri University of Science & Technology Library</a></span></span></span></span></div>