Experimental designs covered in the course include multi-factor randomized designs, block designs, latin-square designs, completely randomized split-plot designs and randomized complete block split-plot designs.
Text: The Elements of Statistical Learning, 2nd Edition Hastie, Tibshirani, Friedman Description: This course covers modern data science techniques, including basic statistical learning theories and their applications. A variety of data mining methodologies, algorithms, and software tools will be introduced, with emphasis on both conceptual and computational aspects.
Applications in bioinformatics, genomics, text mining, social networks, and so on will be covered. This course emphasizes on statistical analysis, methodology, and theory in modern machine learning. It is intended for students who want to practice state-of-art machine learning tools and algorithms, and also understand theoretical principles and statistical properties that underlie the algorithms.
The topics include regression, classification, clustering, dimension reduction, and high dimensional analysis. Published by Wiley, New - Hardcover Condition: new.
New - Hardcover Condition: New. Dowdy, Shirley, Wearden, Stanley, Chilko. Print on Demand. Condition: New. Brand New! This item is printed on demand. From United Kingdom to U. Quantity: Language: English. Brand new Book. Praise for the Second Edition "Statistics for Research has other fine qualities besides superior organization. The examples and the statistical methods are laid out with unusual clarity by the simple device of using special formats for each.
The book was written with great care and is extremely user-friendly. The Third Edition of this bestselling text reflects how the changes in the computing environment have transformed the way statistical analyses are performed today. As in the earlier editions, emphasis is placed on how to select the proper statistical procedure and how to interpret results.
Whenever possible, to avoid using the computer as a "black box" that performs a mysterious process on the data, actual computational procedures are also given. A must for scientists who analyze data, professionals and researchers who need a self-teaching text, and graduate students in statistical methods, Statistics for Research, Third Edition brings the methodology up to date in a very practical and accessible way.
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