Applied regression modeling:
Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Hoboken, NJ, USA
Wiley
2021
|
| Edition: | Third edition |
| Subjects: | |
| Online Access: | DE-188 DE-91 DE-29 Volltext |
| Physical Description: | 1 Online-Ressource (xxi, 310 Seiten) Illustrationen, Diagramme |
| ISBN: | 9781119615903 9781119615880 9781119615941 |
| DOI: | 10.1002/9781119615941 |
Staff View
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| contents | Cover -- Title Page -- Copyright -- Contents -- Preface -- Acknowledgments -- INTRODUCTION -- I.1 Statistics in Practice -- I.2 Learning Statistics -- About the Companion Website -- Chapter 1 Foundations -- 1.1 Identifying and Summarizing Data -- 1.2 Population Distributions -- 1.3 Selecting Individuals at Random-Probability -- 1.4 Random Sampling -- 1.4.1 Central limit theorem-normal version -- 1.4.2 Central limit theorem-t‐version -- 1.5 Interval Estimation -- 1.6 Hypothesis Testing -- 1.6.1 The rejection region method -- 1.6.2 The p‐value method -- 1.6.3 Hypothesis test errors -- 1.7 Random Errors and Prediction -- 1.8 Chapter Summary -- Chapter 2 Simple Linear Regression -- 2.1 PROBABILITY MODEL FOR X and Y -- 2.2 Least Squares Criterion -- 2.3 Model Evaluation -- 2.3.1 Regression standard error -- 2.3.2 Coefficient of determination-R2 -- 2.3.3 Slope parameter -- 2.4 Model Assumptions -- 2.4.1 Checking the model assumptions -- 2.4.2 Testing the model assumptions -- 2.5 Model Interpretation -- 2.6 Estimation and Prediction -- 2.6.1 Confidence interval for the population mean, E(Y) -- 2.6.2 Prediction interval for an individual Y‐value -- 2.7 Chapter Summary -- 2.7.1 Review example -- Chapter 3 Multiple Linear Regression -- 3.1 Probability Model for (X1, X2, …) and Y -- 3.2 Least Squares Criterion -- 3.3 Model Evaluation -- 3.3.1 Regression standard error -- 3.3.2 Coefficient of determination-R2 -- 3.3.3 Regression parameters-global usefulness test -- 3.3.4 Regression parameters-nested model test -- 3.3.5 Regression parameters-individual tests -- 3.4 Model Assumptions -- 3.4.1 Checking the model assumptions -- 3.4.2 Testing the model assumptions -- 3.5 Model Interpretation -- 3.6 Estimation and Prediction -- 3.6.1 Confidence interval for the population mean, E(Y) -- 3.6.2 Prediction interval for an individual Y‐value -- 3.7 Chapter Summary Chapter 4 Regression Model Building I -- 4.1 Transformations -- 4.1.1 Natural logarithm transformation for predictors -- 4.1.2 Polynomial transformation for predictors -- 4.1.3 Reciprocal transformation for predictors -- 4.1.4 Natural logarithm transformation for the response -- 4.1.5 Transformations for the response and predictors -- 4.2 Interactions -- 4.3 Qualitative Predictors -- 4.3.1 Qualitative predictors with two levels -- 4.3.2 Qualitative predictors with three or more levels -- 4.4 Chapter Summary -- Chapter 5 Regression Model Building II -- 5.1 Influential Points -- 5.1.1 Outliers -- 5.1.2 Leverage -- 5.1.3 Cook's distance -- 5.2 Regression Pitfalls -- 5.2.1 Nonconstant variance -- 5.2.2 Autocorrelation -- 5.2.3 Multicollinearity -- 5.2.4 Excluding important predictor variables -- 5.2.5 Overfitting -- 5.2.6 Extrapolation -- 5.2.7 Missing data -- 5.2.8 Power and sample size -- 5.3 Model Building Guidelines -- 5.4 Model Selection -- 5.5 Model Interpretation Using Graphics -- 5.6 Chapter Summary -- NOTATION AND FORMULAS -- UNIVARIATE DATA -- SIMPLE LINEAR REGRESSION -- MULTIPLE LINEAR REGRESSION -- Bibliography -- Glossary -- Index -- EULA. |
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| dewey-full | 519.536 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
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| dewey-tens | 510 - Mathematics |
| discipline | Mathematik Wirtschaftswissenschaften |
| discipline_str_mv | Mathematik Wirtschaftswissenschaften |
| doi_str_mv | 10.1002/9781119615941 |
| edition | Third edition |
| format | Electronic eBook |
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| illustrated | Not Illustrated |
| index_date | 2024-07-03T18:01:24Z |
| indexdate | 2024-09-10T02:22:35Z |
| institution | BVB |
| isbn | 9781119615903 9781119615880 9781119615941 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032844559 |
| oclc_num | 1161998348 |
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| physical | 1 Online-Ressource (xxi, 310 Seiten) Illustrationen, Diagramme |
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| publishDate | 2021 |
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| publisher | Wiley |
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| spelling | Pardoe, Iain 1970- Verfasser (DE-588)1025919025 aut Applied regression modeling Iain Pardoe Third edition Hoboken, NJ, USA Wiley 2021 © 2021 1 Online-Ressource (xxi, 310 Seiten) Illustrationen, Diagramme txt rdacontent c rdamedia cr rdacarrier Regression analysis Regressionsanalyse (DE-588)4129903-6 gnd rswk-swf Regressionsanalyse (DE-588)4129903-6 s DE-604 Erscheint auch als Druck-Ausgabe 978-1-119-61586-6 https://doi.org/10.1002/9781119615941 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Pardoe, Iain 1970- Applied regression modeling Cover -- Title Page -- Copyright -- Contents -- Preface -- Acknowledgments -- INTRODUCTION -- I.1 Statistics in Practice -- I.2 Learning Statistics -- About the Companion Website -- Chapter 1 Foundations -- 1.1 Identifying and Summarizing Data -- 1.2 Population Distributions -- 1.3 Selecting Individuals at Random-Probability -- 1.4 Random Sampling -- 1.4.1 Central limit theorem-normal version -- 1.4.2 Central limit theorem-t‐version -- 1.5 Interval Estimation -- 1.6 Hypothesis Testing -- 1.6.1 The rejection region method -- 1.6.2 The p‐value method -- 1.6.3 Hypothesis test errors -- 1.7 Random Errors and Prediction -- 1.8 Chapter Summary -- Chapter 2 Simple Linear Regression -- 2.1 PROBABILITY MODEL FOR X and Y -- 2.2 Least Squares Criterion -- 2.3 Model Evaluation -- 2.3.1 Regression standard error -- 2.3.2 Coefficient of determination-R2 -- 2.3.3 Slope parameter -- 2.4 Model Assumptions -- 2.4.1 Checking the model assumptions -- 2.4.2 Testing the model assumptions -- 2.5 Model Interpretation -- 2.6 Estimation and Prediction -- 2.6.1 Confidence interval for the population mean, E(Y) -- 2.6.2 Prediction interval for an individual Y‐value -- 2.7 Chapter Summary -- 2.7.1 Review example -- Chapter 3 Multiple Linear Regression -- 3.1 Probability Model for (X1, X2, …) and Y -- 3.2 Least Squares Criterion -- 3.3 Model Evaluation -- 3.3.1 Regression standard error -- 3.3.2 Coefficient of determination-R2 -- 3.3.3 Regression parameters-global usefulness test -- 3.3.4 Regression parameters-nested model test -- 3.3.5 Regression parameters-individual tests -- 3.4 Model Assumptions -- 3.4.1 Checking the model assumptions -- 3.4.2 Testing the model assumptions -- 3.5 Model Interpretation -- 3.6 Estimation and Prediction -- 3.6.1 Confidence interval for the population mean, E(Y) -- 3.6.2 Prediction interval for an individual Y‐value -- 3.7 Chapter Summary Chapter 4 Regression Model Building I -- 4.1 Transformations -- 4.1.1 Natural logarithm transformation for predictors -- 4.1.2 Polynomial transformation for predictors -- 4.1.3 Reciprocal transformation for predictors -- 4.1.4 Natural logarithm transformation for the response -- 4.1.5 Transformations for the response and predictors -- 4.2 Interactions -- 4.3 Qualitative Predictors -- 4.3.1 Qualitative predictors with two levels -- 4.3.2 Qualitative predictors with three or more levels -- 4.4 Chapter Summary -- Chapter 5 Regression Model Building II -- 5.1 Influential Points -- 5.1.1 Outliers -- 5.1.2 Leverage -- 5.1.3 Cook's distance -- 5.2 Regression Pitfalls -- 5.2.1 Nonconstant variance -- 5.2.2 Autocorrelation -- 5.2.3 Multicollinearity -- 5.2.4 Excluding important predictor variables -- 5.2.5 Overfitting -- 5.2.6 Extrapolation -- 5.2.7 Missing data -- 5.2.8 Power and sample size -- 5.3 Model Building Guidelines -- 5.4 Model Selection -- 5.5 Model Interpretation Using Graphics -- 5.6 Chapter Summary -- NOTATION AND FORMULAS -- UNIVARIATE DATA -- SIMPLE LINEAR REGRESSION -- MULTIPLE LINEAR REGRESSION -- Bibliography -- Glossary -- Index -- EULA. Regression analysis Regressionsanalyse (DE-588)4129903-6 gnd |
| subject_GND | (DE-588)4129903-6 |
| title | Applied regression modeling |
| title_auth | Applied regression modeling |
| title_exact_search | Applied regression modeling |
| title_exact_search_txtP | Applied regression modeling |
| title_full | Applied regression modeling Iain Pardoe |
| title_fullStr | Applied regression modeling Iain Pardoe |
| title_full_unstemmed | Applied regression modeling Iain Pardoe |
| title_short | Applied regression modeling |
| title_sort | applied regression modeling |
| topic | Regression analysis Regressionsanalyse (DE-588)4129903-6 gnd |
| topic_facet | Regression analysis Regressionsanalyse |
| url | https://doi.org/10.1002/9781119615941 |
| work_keys_str_mv | AT pardoeiain appliedregressionmodeling |