9781642955743-1642955744-Preparing Data for Analysis with JMP

Preparing Data for Analysis with JMP

ISBN-13: 9781642955743
ISBN-10: 1642955744
Author: Robert Carver
Publication date: 2019
Publisher: SAS Institute
Format: Paperback 216 pages
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Book details

ISBN-13: 9781642955743
ISBN-10: 1642955744
Author: Robert Carver
Publication date: 2019
Publisher: SAS Institute
Format: Paperback 216 pages

Summary

Preparing Data for Analysis with JMP (ISBN-13: 9781642955743 and ISBN-10: 1642955744), written by authors Robert Carver, was published by SAS Institute in 2019. With an overall rating of 3.9 stars, it's a notable title among other Data Mining (Databases & Big Data, Mathematical & Statistical, Software, Enterprise Applications) books. You can easily purchase or rent Preparing Data for Analysis with JMP (Paperback) from BooksRun, along with many other new and used Data Mining books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.44.

Description

Access and clean up data easily using JMP!

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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