Applied Regression Analysis and Experimental Design
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A01=Gregory C. Arnold
A01=Richard J. Brook
advanced regression experimental design guide
ANOVA Table
Author_Gregory C. Arnold
Author_Richard J. Brook
Balanced Incomplete Block Design
BCD
Category=PBT
Correlation Form
Data Set
Dummy Variables
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
Experimental Design Models
Experimental Units
hypothesis testing methods
Incomplete Block Design
Lactation Records
least squares estimation
linear statistical modeling
Main Plot
Main Plot Treatment
multivariate analysis techniques
Potato Experiment
Prediction Curve
Predictor Variables
principal component analysis
Pure Error
Ridge Estimators
Ridge Trace
Ruahine Ranges
Serum Gamma Glutamyl Transpeptidase
Split Plot Experiment
SSE
Sub-plot Treatments
vector geometry applications
VIF
Watering Treatment
Product details
- ISBN 9780824772529
- Weight: 630g
- Dimensions: 152 x 229mm
- Publication Date: 25 Apr 1985
- Publisher: Taylor & Francis Inc
- Publication City/Country: US
- Product Form: Hardback
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For a solid foundation of important statistical methods, the concise, single-source text unites linear regression with analysis of experiments and provides students with the practical understanding needed to apply theory in real data analysis problems.Stressing principles while keeping computational and theoretical details at a manageable level, Applied Regression Analysis and Experimental Design features an emphasis on vector geometry and least squares to unify and provide an intuitive basis for most topics covered… abundant examples and exercises using real-life data sets clearly illustrating practical of data analysis…essential exposure to MINITAB and GENSTAT computer packages , including computer printouts…and important background material such as vector and matrix properties and the distributional properties of quadratic forms.Designed to make theory work for students, this clearly written, easy-to-understand work serves as the ideal texts for courses Regression, Experimental Design, and Linear Models in a broad range of disciplines. Moreover, applied statisticians will find the book a useful reference for the general application of the linear model.
Brook, Richard J.; Arnold, Gregory C.
