000 02257 a2200289 4500
001 1351202251
005 20250317100408.0
008 250312042018xx 133 eng
020 _a9781351202251
037 _bTaylor & Francis
_cGBP 47.99
_fBB
040 _a01
041 _aeng
072 7 _aJMB
_2thema
072 7 _aPBT
_2thema
072 7 _aJMB
_2bic
072 7 _aPBT
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072 7 _aMAT029000
_2bisac
072 7 _aBUS061000
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072 7 _aREF000000
_2bisac
100 1 _aKimmo Vehkalahti
245 1 0 _aMultivariate Analysis for the Behavioral Sciences, Second Edition
250 _a2
260 _bCRC Press
_c20181219
300 _a437 p
520 _bMultivariate Analysis for the Behavioral Sciences, Second Edition is designed to show how a variety of statistical methods can be used to analyse data collected by psychologists and other behavioral scientists. Assuming some familiarity with introductory statistics, the book begins by briefly describing a variety of study designs used in the behavioral sciences, and the concept of models for data analysis. The contentious issues of p -values and confidence intervals are also discussed in the introductory chapter. After describing graphical methods, the book covers regression methods, including simple linear regression, multiple regression, locally weighted regression, generalized linear models, logistic regression, and survival analysis. There are further chapters covering longitudinal data and missing values, before the last seven chapters deal with multivariate analysis, including principal components analysis, factor analysis, multidimensional scaling, correspondence analysis, and cluster analysis. Features: Presents an accessible introduction to multivariate analysis for behavioral scientists Contains a large number of real data sets, including cognitive behavioral therapy, crime rates, and drug usage Includes nearly 100 exercises for course use or self-study Supplemented by a GitHub repository with all datasets and R code for the examples and exercises Theoretical details are separated from the main body of the text Suitable for anyone working in the behavioral sciences with a basic grasp of statistics
700 1 _aBrian S. Everitt
_4A01
999 _c2021
_d2021