Regression basics:
Although many people have PCs with software capable of performing regression techniques, only a few know how to capitalize on the flexibility and wide application of regression analysis. This book shows readers how to get the most from regression by providing a friendly, non-technical introduction t...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Thousand Oaks [u.a.]
Sage
2001
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| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Zusammenfassung: | Although many people have PCs with software capable of performing regression techniques, only a few know how to capitalize on the flexibility and wide application of regression analysis. This book shows readers how to get the most from regression by providing a friendly, non-technical introduction to the subject. Accessible to anyone with only an introductory statistics background, the book begins with the simplest, two-variable linear model and gradually builds towards models of more complexity, such as multivariate regression. Kahane uses three engaging examples to illustrate regression concepts. These examples show the creative way in which regression analysis can be used to determine why some professional sports players earn higher salaries than others, the factors that affect voting patterns in presidential elections, and how to determine the factors that explain differences in abortion rates. Data for these examples are provided in an Appendix so that readers can have tangible, hands-on experience in performing linear regression analysis. |
| Beschreibung: | XI, 201 S. graph. Darst. |
| ISBN: | 0761919589 0761924132 |
Internformat
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| 520 | 3 | |a Although many people have PCs with software capable of performing regression techniques, only a few know how to capitalize on the flexibility and wide application of regression analysis. This book shows readers how to get the most from regression by providing a friendly, non-technical introduction to the subject. Accessible to anyone with only an introductory statistics background, the book begins with the simplest, two-variable linear model and gradually builds towards models of more complexity, such as multivariate regression. Kahane uses three engaging examples to illustrate regression concepts. These examples show the creative way in which regression analysis can be used to determine why some professional sports players earn higher salaries than others, the factors that affect voting patterns in presidential elections, and how to determine the factors that explain differences in abortion rates. Data for these examples are provided in an Appendix so that readers can have tangible, hands-on experience in performing linear regression analysis. | |
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Datensatz im Suchindex
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|---|---|
| adam_text | CONTENTS
Acknowledgments vii
Preface ix
Chapter 1: An Introduction to the Linear Regression Model 1
Baseball Salaries 1
Linear Regression Model Assumption 3
Population Data Versus Sample Data 8
Presidential Elections 10
Abortion Rates 12
Types of Data Sets 14
Notes 15
Problems 17
Chapter 2: The Least Squares Estimation Method:
Fitting Lines to Data 19
Ordinary Least Squares 19
Regression Model Assumptions and the Properties of
Ordinary Least Squares 30
Summing Up 34
Notes 34
Problems 36
Chapter 3: Model Performance and Evaluation 37
Goodness of Fit: The R2 37
Sample Results and Population Parameters 43
Summing Up 54
Notes 55
Problems 58
Chapter 4: Multiple Regression Analysis 59
Baseball Salaries Revisited 59
Presidential Elections Revisited 66
Abortion Rates Revisited 68
Further Considerations for the Multiple Regression Model 72
Summing Up 73
Notes 74
Problems 76
Chapter 5: Nonlinear, Dummy, Interaction, and Time Variables 79
Nonlinear Independent Variables 79
Dummy Independent Variables 83
Interaction Variables 92
Time as an Independent Variable 101
Summing Up 107
Notes 108
Problems 110
Chapter 6: Some Common Problems in Regression Analysis 113
The Problem of High Multicollinearity 113
Nonconstant Error Variance 119
Autocorrelated Errors 127
Notes 132
Problems 133
Chapter 7: Where to Go From HERE 135
Key Points to Bear in Mind 135
Other Topics in Regression Analysis 136
Go Forward and Regress! 138
Notes 138
Appendix A: Data Sets Used in Examples 139
Appendix B: Instructions for Using Excel and SPSS 151
Using Excel 151
Using SPSS 158
Notes 161
Appendix C: t Table 163
Appendix D: Answers to Problems 165
Glossary 187
References 197
Index 199
About the Author 202
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| indexdate | 2024-07-09T19:17:20Z |
| institution | BVB |
| isbn | 0761919589 0761924132 |
| language | English |
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| physical | XI, 201 S. graph. Darst. |
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| spelling | Kahane, Leo H. Verfasser aut Regression basics Leo H. Kahane Thousand Oaks [u.a.] Sage 2001 XI, 201 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Although many people have PCs with software capable of performing regression techniques, only a few know how to capitalize on the flexibility and wide application of regression analysis. This book shows readers how to get the most from regression by providing a friendly, non-technical introduction to the subject. Accessible to anyone with only an introductory statistics background, the book begins with the simplest, two-variable linear model and gradually builds towards models of more complexity, such as multivariate regression. Kahane uses three engaging examples to illustrate regression concepts. These examples show the creative way in which regression analysis can be used to determine why some professional sports players earn higher salaries than others, the factors that affect voting patterns in presidential elections, and how to determine the factors that explain differences in abortion rates. Data for these examples are provided in an Appendix so that readers can have tangible, hands-on experience in performing linear regression analysis. Analyse de régression Regressieanalyse gtt Regression Analysis Regression analysis Regressionsanalyse (DE-588)4129903-6 gnd rswk-swf Regressionsanalyse (DE-588)4129903-6 s DE-604 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=010474518&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Kahane, Leo H. Regression basics Analyse de régression Regressieanalyse gtt Regression Analysis Regression analysis Regressionsanalyse (DE-588)4129903-6 gnd |
| subject_GND | (DE-588)4129903-6 |
| title | Regression basics |
| title_auth | Regression basics |
| title_exact_search | Regression basics |
| title_full | Regression basics Leo H. Kahane |
| title_fullStr | Regression basics Leo H. Kahane |
| title_full_unstemmed | Regression basics Leo H. Kahane |
| title_short | Regression basics |
| title_sort | regression basics |
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