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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
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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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
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