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:
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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