9781635261486_

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 organizations 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 JMPs 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

(*_*)9781635261486_

Access and clean up data easily using JMP!

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 JMPs 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

...

Preparing Data for Analysis with JMP

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