Analysis of Variance, Design, and Regression

Regular price €137.99
Quantity:
Ships in 10-20 days
Delivery/Collection within 10-20 working days
Shipping & Delivery
A01=Ronald Christensen
advanced linear modeling for scientific research
ANOVA
ANOVA Model
Author_Ronald Christensen
Balanced Incomplete Block Design
Category=JMB
Category=PBKB
Category=PBT
Coleman Report Data
Confidence Interval
data analysis course
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
Error Line
Error Sums
Extensions to generalized linear models
Full Model
general additive and generalized additive models
generalized additive models
lasso regression techniques
Latin Square Designs
linear structures for modeling data
Log Linear Models
logistic regression analysis
LS
Moisture Content
nonparametric and lasso regression
nonparametric methods
Normal Plot
Null Hypotheses
Null Model
Partition Set
Prediction Interval
Predictor Variable
Principal Components Regression
Reference Distribution
Regression Model
Sample Correlations
Simple Linear Regression Model
split plot analyses
SSE
statistical modeling
unbalanced data
unbalanced experimental design
Variance Table
Verbal Test Scores

Product details

  • ISBN 9781498730143
  • Weight: 1680g
  • Dimensions: 178 x 254mm
  • Publication Date: 22 Dec 2015
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
Secure checkout Fast Shipping Easy returns

Analysis of Variance, Design, and Regression: Linear Modeling for Unbalanced Data, Second Edition presents linear structures for modeling data with an emphasis on how to incorporate specific ideas (hypotheses) about the structure of the data into a linear model for the data. The book carefully analyzes small data sets by using tools that are easily scaled to big data. The tools also apply to small relevant data sets that are extracted from big data.

New to the Second Edition

  • Reorganized to focus on unbalanced data
  • Reworked balanced analyses using methods for unbalanced data
  • Introductions to nonparametric and lasso regression
  • Introductions to general additive and generalized additive models
  • Examination of homologous factors
  • Unbalanced split plot analyses
  • Extensions to generalized linear models
  • R, Minitab®, and SAS code on the author’s website

The text can be used in a variety of courses, including a yearlong graduate course on regression and ANOVA or a data analysis course for upper-division statistics students and graduate students from other fields. It places a strong emphasis on interpreting the range of computer output encountered when dealing with unbalanced data.

Ronald Christensen is a professor of statistics in the Department of Mathematics and Statistics at the University of New Mexico. Dr. Christensen is a fellow of the American Statistical Association (ASA) and Institute of Mathematical Statistics. He is a past editor of The American Statistician and a past chair of the ASA’s Section on Bayesian Statistical Science. His research interests include linear models, Bayesian inference, log-linear and logistic models, and statistical methods.

More from this author