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00000nam c2200205 k 4500
000003858167
20220731102334
050127s2004 us 0 eng
▼a 0071232524
▼a 123456
▼c 123456
▼d 211070
▼l WM6153
▼a QA278.2
▼a QA278.2
▼b N46
▼a Kutner,Michael H
▼a Applied Linear Regression Models/
▼d Kutner,Michael H;
▼e Nachtsheim,Christopher J;
▼e Neter,John.
▼a 4th ed.
▼a Boston:
▼b McGraw-Hill,
▼c 2004.
▼a 701p.;
▼c 23cm+
▼e CD-ROM.
▼a Regression analysis
▼a Christopher J,Nachtsheim
▼a John ,Neter
▼b US$35
▼a 단행본
| 자료유형 : | 단행본 |
|---|---|
| ISBN : | 0071232524 |
| 분류기호 : | QA278.2 |
| 개인저자 : | Kutner,Michael H |
| 서명/저자사항 : | Applied Linear Regression Models/ Kutner,Michael H; Nachtsheim,Christopher J; Neter,John. |
| 판사항 : | 4th ed. |
| 발행사항 : | Boston: McGraw-Hill, 2004. |
| 형태사항 : | 701p.; 23cm+ CD-ROM. |
| 개인저자 : | Christopher J,Nachtsheim |
| 개인저자 : | John ,Neter |
| 언어 | 영어 |
Part One : Simple Linear Regression
1. Linear Regression with One Predictor Variable
2. Inferences in Regression and Correlation Analysis
3. Diagnostics and Remedial Measures
4. Simultaneous Inferences and Other Topics in Regression Analysis
5. Matrix Approach to Simple Linear Regression Analysis
Part Two : Multiple Linear Regression
6. Multiple Regression I
7. Multiple Regression II
8. Regression Models for Quantitative and Qualitative Predictors
9. Building the Regression Model I : Model Selection and Validation
10. Building the Regression Model II : Diagnostics
11. Building the Regression Model III : Remedial Measures
12. Autocorrelation in Time Series Data
Part Three : Nonlinear Regression
13. Introduction to Nonlinear Regression and Neural Networks
14. Logistic Regression, Poisson Regression, and Generalized Linear Models
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