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Example-rich and experiment-driven, Genetic Analysis of Complex Traits Using SAS demonstrates how you can use SAS and SAS/Genetics to extract answers from your quantitative and molecular genetics data. The book guides you through the mix of genetic, statistical, and SAS skills that are needed, enabling you to apply what you've learned to your own experimental data. You'll find this an invaluable resource whether you are a researcher, scientist, graduate student, bioinformatician, or statistician--or any other SAS user interested in joining the highly active and exciting field of genetic analysis. Publisher.

SAS (Computer file) --- Molecular genetics. --- Quantitative genetics. --- SAS (Computer file). --- Quantitative genetics --- Molecular genetics --- Genetics --- Molecular biology --- Quantitative inheritance --- Statistical analysis system --- SAS system --- Statistics --- Quantitative Genetics --- SAS

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This contemporary presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The authors demonstrate how to analyze data—showing code, graphics, and accompanying computer listings—for all the methods they cover. They emphasize how to construct and interpret graphs, discuss principles of graphical design, and show how accompanying traditional tabular results are used to confirm the visual impressions derived directly from the graphs. Many of the graphical formats are novel and appear here for the first time in print. All chapters have exercises. This book can serve as a standalone text for statistics majors at the master's level and for other quantitatively oriented disciplines at the doctoral level, and as a reference book for researchers. In-depth discussions of regression analysis, analysis of variance, and design of experiments are followed by introductions to analysis of discrete bivariate data, nonparametrics, logistic regression, and ARIMA time series modeling. The authors illustrate classical concepts and techniques with a variety of case studies using both newer graphical tools and traditional tabular displays. The authors provide and discuss S-Plus, R, and SAS executable functions and macros for all new graphical display formats. All graphs and tabular output in the book were constructed using these programs. Complete transcripts for all examples and figures are provided for readers to use as models for their own analyses. Richard M. Heiberger and Burt Holland are both Professors in the Department of Statistics at Temple University and elected Fellows of the American Statistical Association. Richard M. Heiberger participated in the design of the S-Plus linear model and analysis of variance commands while on research leave at Bell Labs in 1987–88 and has been closely involved as a beta tester and user of S-Plus. Burt Holland has made many research contributions to linear modeling and simultaneous statistical inference, and frequently serves as a consultant to medical investigators. Both teach the Temple University course sequence that inspired them to write this text.

Mathematical statistics --- Statistics --- R (Computer program language) --- Data processing --- S-Plus --- SAS (Computer file) --- regressie-analyse --- tijdreeksanalyse --- wiskundige statistiek --- 519.2 --- -Statistics --- -R (Computer program language) --- 519.50285 --- GNU-S (Computer program language) --- Domain-specific programming languages --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Statistical inference --- Statistics, Mathematical --- Probabilities --- Sampling (Statistics) --- Probability. Mathematical statistics --- S-Plus. --- Statistical analysis system --- SAS system --- SPlus --- 519.2 Probability. Mathematical statistics --- Probabilities. --- Statistics . --- Probability Theory and Stochastic Processes. --- Statistical Theory and Methods. --- Probability --- Combinations --- Chance --- Least squares --- Risk --- Mathematical statistics - Data processing --- Statistics - Data processing