Name: Making Sense Of Data I: A Practical Guide To Exploratory Data Analysis And Data Mining, 2Nd Edition
Price: 79.27 EUR
Availability: InStock
Author: Glenn J. Myatt, Wayne P. Johnson
ISBN: 9781118407417

portada Making Sense Of Data I: A Practical Guide To Exploratory Data Analysis And Data Mining, 2Nd Edition

Making Sense Of Data I: A Practical Guide To Exploratory Data Analysis And Data Mining, 2Nd Edition

Type

Physical Book

Publisher

Wiley

Author

Glenn J. Myatt, Wayne P. Johnson

Topic

Us Gr

Pages

248

Dimensions

15.24 x 22.86 cm.

ISBN

1118407415

ISBN13

9781118407417

Synopsis "Making Sense Of Data I: A Practical Guide To Exploratory Data Analysis And Data Mining, 2Nd Edition"

With A Focus On The Needs Of Educators And Students, Making Sense Of Data Presents The Steps And Issues That Need To Be Considered In Order To Successfully Complete A Data Analysis Or Data Mining Project. This Second Edition Focuses On Basic Data Analysis Approaches That Are Necessary To Complete A Diverse Range Of Projects. New Examples Have Been Added To Illustrate The Different Approaches, And There Is Considerably More Emphasis On Hands - On Software Tutorials To Provide Real - World Exercises. Via The Related Web Site, The Book Is Accompanied By Traceis Software, Data Sets, And Tutorials; Powerpoint Slides For Classroom Use; And Other Supplementary Material To Support Educational Classes. The Authors Provide Clear Explanations That Guide Readers To Make Timely And Accurate Decisions From Data In Almost Every Field Of Study. A Step - By - Step Approach Aids Professionals In Carefully Analyzing Data And Implementing Results, Leading To The Development Of Smarter Business Decisions. The Topical Coverage Has Been Revised Throughout To Ensure Only Basic Data Analysis Approaches Are Discussed, And New Appendices Have Been Added On The Traceis Software As Well As New Tutorials Using A Variety Of Data Sets With The Software. Additional Examples Of Data Preparation, Tables Of Graphs, Statistics, Grouping, And Prediction Have Been Included, And The Topics Of Multiple Linear Regression And Logistic Regression Have Been Added To Provide A Range Of Widely Used And Transparent Approaches To Performing Classification And Regression