Articoli correlati a Preparing Data for Analysis with JMP (Hardcover edition)

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9781642955743: Preparing Data for Analysis with JMP (Hardcover edition)

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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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Altre edizioni note dello stesso titolo

9781629604183: Preparing Data for Analysis with JMP

Edizione in evidenza

ISBN 10:  1629604186 ISBN 13:  9781629604183
Casa editrice: SAS Institute, 2017
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