Published by CreateSpace Independent Publishing Platform, 2017
ISBN 10: 1541188500 ISBN 13: 9781541188501
Language: English
Seller: Best Price, Torrance, CA, U.S.A.
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Published by CreateSpace Independent Publishing Platform, 2017
ISBN 10: 1544038682 ISBN 13: 9781544038681
Language: English
Seller: ThriftBooks-Dallas, Dallas, TX, U.S.A.
Paperback. Condition: As New. No Jacket. Pages are clean and are not marred by notes or folds of any kind. ~ ThriftBooks: Read More, Spend Less 1.27.
Published by Liosngate Pictures Entertainment 2014-05-13 00:00:00, 2014
Seller: R Bookmark, Youngtown, AZ, U.S.A.
blu ray. Condition: Used - Good.
Seller: Romtrade Corp., STERLING HEIGHTS, MI, U.S.A.
Condition: New. Brand New. Soft Cover International Edition. Different ISBN and Cover Image. Priced lower than the standard editions which is usually intended to make them more affordable for students abroad. The core content of the book is generally the same as the standard edition. The country selling restrictions may be printed on the book but is no problem for the self-use. This Item maybe shipped from US or any other country as we have multiple locations worldwide.
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: New.
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Seller: Lakeside Books, Benton Harbor, MI, U.S.A.
Condition: New. Brand New! Not Overstocks or Low Quality Book Club Editions! Direct From the Publisher! We're not a giant, faceless warehouse organization! We're a small town bookstore that loves books and loves it's customers! Buy from Lakeside Books!
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Add to basketPaperback. Condition: Brand New. 428 pages. 9.00x6.00x0.97 inches. In Stock.
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Add to basketPaperback. Condition: Brand New. 279 pages. 9.75x6.75x0.75 inches. In Stock.
ISBN 10: 7302557004 ISBN 13: 9787302557005
Seller: liu xing, Nanjing, JS, China
paperback. Condition: New. Paperback. Pub Date: 2020-07-01 Pages: 528 Publisher: Tsinghua University Press How to use R language for advanced data analysis. the techniques involved include generalized linear models. generalized additive models. mixed-effects models. machine learning. parallelism Processing How to use R language data visualization technology to achieve regression. such as linear regression and advanced regression. and understand regression splines and additive models How to use R language to implement m.