This textbook considers statistical learning applications when
interest centers on the conditional distribution of the response
variable, given a set of predictors, and when it is important to
characterize how the predictors are related to the response. This
fully revised new edition includes important developments over the
past 8 years. Consistent with modern data analytics, it emphasizes
that a proper statistical learning data analysis derives from sound
data collection, intelligent data management, appropriate statistical
procedures, and an accessible interpretation of results. As in the
first edition, a unifying theme is supervised learning that can be
treated as a form of regression analysis. Key concepts and procedures
are illustrated with real applications, especially those with
practical implications. The material is written for upper
undergraduate level and graduate students in the social and life
sciences and for researchers who want to apply statistical learning
procedures to scientific and policy problems. The author uses this
book in a course on modern regression for the social, behavioral, and
biological sciences. All of the analyses included are done in R with
code routinely provided.
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Produktdetaljer
ISBN
9783319440484
Publisert
2017
Utgave
2. utgave
Utgiver
Vendor
Springer
Språk
Product language
Engelsk
Format
Product format
Digital bok
Forfatter