Description

Book Synopsis

The Workflow of Data Analysis Using Stata, by J. Scott Long, is an essential productivity tool for data analysts. Long presents lessons gained from his experience and demonstrates how to design and implement efficient workflows for both one-person projects and team projects. After introducing workflows and explaining how a better workflow can make it easier to work with data, Long describes planning, organizing, and documenting your work. He then introduces how to write and debug Stata do-files and how to use local and global macros. After a discussion of conventions that greatly simplify data analysis the author covers cleaning, analyzing, and protecting data.



Table of Contents

Introduction. Planning, Organizing, and Documenting. Writing and Debugging Do-Files. Automating Your Work. Names, Notes, and Labels. Cleaning Your Data. Analyzing Data and Presenting Results. Protecting Your files. References.

The Workflow of Data Analysis Using Stata

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    £999.99

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    A Paperback / softback by J. Scott Long

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      View other formats and editions of The Workflow of Data Analysis Using Stata by J. Scott Long

      Publisher: Stata Press
      Publication Date: Publication Date: 10/12/2008
      ISBN13: 9781597180474, 978-1597180474
      ISBN10: 1597180475

      Description

      Book Synopsis

      The Workflow of Data Analysis Using Stata, by J. Scott Long, is an essential productivity tool for data analysts. Long presents lessons gained from his experience and demonstrates how to design and implement efficient workflows for both one-person projects and team projects. After introducing workflows and explaining how a better workflow can make it easier to work with data, Long describes planning, organizing, and documenting your work. He then introduces how to write and debug Stata do-files and how to use local and global macros. After a discussion of conventions that greatly simplify data analysis the author covers cleaning, analyzing, and protecting data.



      Table of Contents

      Introduction. Planning, Organizing, and Documenting. Writing and Debugging Do-Files. Automating Your Work. Names, Notes, and Labels. Cleaning Your Data. Analyzing Data and Presenting Results. Protecting Your files. References.

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