Applied linear regression

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John Wiley & Sons Canada, Limited, 1980 - Mathematics - 283 pages
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Simple linear regression; Multiple regression; Drawing conclusions; Weighted least squares, testing for lack of fit, general F-tests, and confidence ellipsoids; Case analysis I: residuals and influence; Case analysis II: symptoms and remedies; Model building I: defining new variables; Model building II: collinearity and variable selection; Prediction; Incomplete data; Nonleast squares estimation.

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Contents

Simple linear regression
1
Multiple regression
31
Drawing conclusions
58
Copyright

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About the author (1980)

Sanford Weisberg is Professor of Statistics at the University of Minnesota, Twin Cities. He is also director of the University's Statistical Consulting Service for Liberal Arts, and has worked with literally hundreds of social scientists and others on the statistical aspects of their research. Professor Weisberg earned a BA in Statistics from the University of California, Berkeley, and a Ph.D. also in statistics from Harvard University, under the direction of Frederick Mosteller. The author of more than sixty articles, his research has primarily been in the areas of regression analysis, including graphical methods, regression diagnostics, and statistical computing. He is a Fellow of the American Statistical Association and former Chair of its Statistical Computing Section. He is the author or co-author of several books, including Applied Linear Regression (third edition 2005, Wiley), Residuals and Influence in Regression (with R. D. Cook, 1982, Chapman & Hall), Applied Regression Including Computing and Graphics (with R. D. Cook, 1999 Wiley). He has several publications in areas that use statistics including archeology, plant sciences, wildlife management, fisheries, and public affairs.

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