Douglas C. Montgomery (Georgia Institute of Technology), Elizabeth A. Peck (The Coca-Cola Company), G. Geoffrey Vining (Virginia Polytechnic and State University)
Introduction to Linear Regression Analysis, 6e Solutions Manual
Herausgegeben:Ryan, Anne G.
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Douglas C. Montgomery (Georgia Institute of Technology), Elizabeth A. Peck (The Coca-Cola Company), G. Geoffrey Vining (Virginia Polytechnic and State University)
Introduction to Linear Regression Analysis, 6e Solutions Manual
Herausgegeben:Ryan, Anne G.
- Broschiertes Buch
INTRODUCTION TO LINEAR REGRESSION ANALYSIS
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Produktdetails
- Produktdetails
- Verlag: Wiley / Wiley & Sons
- Artikelnr. des Verlages: 1W119578690
- 6. Aufl.
- Seitenzahl: 144
- Erscheinungstermin: 15. September 2022
- Englisch
- Abmessung: 180mm x 254mm x 15mm
- Gewicht: 300g
- ISBN-13: 9781119578697
- ISBN-10: 1119578698
- Artikelnr.: 60069885
- Verlag: Wiley / Wiley & Sons
- Artikelnr. des Verlages: 1W119578690
- 6. Aufl.
- Seitenzahl: 144
- Erscheinungstermin: 15. September 2022
- Englisch
- Abmessung: 180mm x 254mm x 15mm
- Gewicht: 300g
- ISBN-13: 9781119578697
- ISBN-10: 1119578698
- Artikelnr.: 60069885
DOUGLAS C. MONTGOMERY, PHD, is Regents Professor of Industrial Engineering and Statistics at Arizona State University. Dr. Montgomery is the co-author of several Wiley books including Introduction to Linear Regression Analysis, 5th Edition. ELIZABETH A. PECK, PHD, is Logistics Modeling Specialist at the Coca-Cola Company in Atlanta, Georgia. G. GEOFFREY VINING, PHD, is Professor in the Department of Statistics at Virginia Polytechnic and State University. Dr. Peck is co-author of Introduction to Linear Regression Analysis, 5th Edition.
Preface vii
2 Simple Linear Regression 1
3 Multiple Linear Regression 13
4 Model Adequacy Checking 29
5 Transformations and Weighting to Correct Model Inadequacies 59
6 Diagnostics for Leverage and Influence 74
7 Polynomial Regression Models 79
8 Indicator Variables 86
9 Multicollinearity 95
10 Variable Selection and Model Building 100
11 Validation of Regression Models 105
12 Introduction to Nonlinear Regression 108
13 Generalized Linear Models 113
14 Regression Analysis of Time Series Data 121
15 Other Topics in the Use of Regression Analysis 125
2 Simple Linear Regression 1
3 Multiple Linear Regression 13
4 Model Adequacy Checking 29
5 Transformations and Weighting to Correct Model Inadequacies 59
6 Diagnostics for Leverage and Influence 74
7 Polynomial Regression Models 79
8 Indicator Variables 86
9 Multicollinearity 95
10 Variable Selection and Model Building 100
11 Validation of Regression Models 105
12 Introduction to Nonlinear Regression 108
13 Generalized Linear Models 113
14 Regression Analysis of Time Series Data 121
15 Other Topics in the Use of Regression Analysis 125
Preface vii
2 Simple Linear Regression 1
3 Multiple Linear Regression 13
4 Model Adequacy Checking 29
5 Transformations and Weighting to Correct Model Inadequacies 59
6 Diagnostics for Leverage and Influence 74
7 Polynomial Regression Models 79
8 Indicator Variables 86
9 Multicollinearity 95
10 Variable Selection and Model Building 100
11 Validation of Regression Models 105
12 Introduction to Nonlinear Regression 108
13 Generalized Linear Models 113
14 Regression Analysis of Time Series Data 121
15 Other Topics in the Use of Regression Analysis 125
2 Simple Linear Regression 1
3 Multiple Linear Regression 13
4 Model Adequacy Checking 29
5 Transformations and Weighting to Correct Model Inadequacies 59
6 Diagnostics for Leverage and Influence 74
7 Polynomial Regression Models 79
8 Indicator Variables 86
9 Multicollinearity 95
10 Variable Selection and Model Building 100
11 Validation of Regression Models 105
12 Introduction to Nonlinear Regression 108
13 Generalized Linear Models 113
14 Regression Analysis of Time Series Data 121
15 Other Topics in the Use of Regression Analysis 125