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Linear Models with Python offers up-to-date insight on essential data analysis topics, from estimation, inference, and prediction to missing data, factorial models, and block designs. Numerous examples illustrate how to apply the different methods using Python

Produktbeschreibung
Linear Models with Python offers up-to-date insight on essential data analysis topics, from estimation, inference, and prediction to missing data, factorial models, and block designs. Numerous examples illustrate how to apply the different methods using Python


Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Autorenporträt
Julian J. Faraway is a professor of statistics in the Department of Mathematical Sciences at the University of Bath. His research focuses on the analysis of functional and shape data with particular application to the modeling of human motion. He earned a PhD in statistics from the University of California, Berkeley.

Rezensionen
'Multiple Python program scripts and screenshots of the outcomes fill the book, and each chapter suggests numerous exercises for training in coding. The book presents an amazingly valuable source of knowledge on statistical modeling and Python tools for students and practitioners.'

- Stan Lipovetsky, Technometrics, Vol 63, Issue 3 2021

'Therefore, this book is very valuable for understanding paired and multivariate linear regressions.[...] The book is clearly structured, containing all the necessary theoretical calculations and theoretical results on which the calculations are based'

- Igor Malyk, International Society for Clinical Biostatistics, 72, 2021