9781629604183-1629604186-Preparing Data for Analysis with JMP

Preparing Data for Analysis with JMP

ISBN-13: 9781629604183
ISBN-10: 1629604186
Author: Robert Carver
Publication date: 2017
Publisher: SAS Institute
Format: Paperback 216 pages
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Book details

ISBN-13: 9781629604183
ISBN-10: 1629604186
Author: Robert Carver
Publication date: 2017
Publisher: SAS Institute
Format: Paperback 216 pages

Summary

Preparing Data for Analysis with JMP (ISBN-13: 9781629604183 and ISBN-10: 1629604186), written by authors Robert Carver, was published by SAS Institute in 2017. With an overall rating of 3.5 stars, it's a notable title among other Mathematical & Statistical (Software) books. You can easily purchase or rent Preparing Data for Analysis with JMP (Paperback) from BooksRun, along with many other new and used Mathematical & Statistical books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

Data acquisition and preparation commonly consume approximately 75% of the effort and time of total data analysis. JMP provides many visual, intuitive, and even innovative data-preparation capabilities that enable you to make the most of your organization's data.

Preparing Data for Analysis with JMP® is organized within a framework of statistical investigations and model-building and illustrates the new data-handling features in JMP, such as the Query Builder. Useful to students and programmers with little or no JMP experience, or those looking to learn the new data-management features and techniques, it uses a practical approach to getting started with plenty of examples. Using step-by-step demonstrations and screenshots, this book walks you through the most commonly used data-management techniques that also include lots of tips on how to avoid common problems.

With this book, you will learn how to:

  • Manage database operations using the JMP Query Builder
  • Get data into JMP from other formats, such as Excel, csv, SAS, HTML, JSON, and the web
  • Identify and avoid problems with the help of JMP’s visual and automated data-exploration tools
  • Consolidate data from multiple sources with Query Builder for tables
  • Deal with common issues and repairs that include the following tasks:
    • reshaping tables (stack/unstack)
    • managing missing data with techniques such as imputation and Principal Components Analysis
    • cleaning and correcting dirty data
    • computing new variables
    • transforming variables for modelling
    • reconciling time and date
  • Subset and filter your data
  • Save data tables for exchange with other platforms
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