Workflow of Data Analysis Using Stata

Häftad, Engelska, 2008

950 kr

Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

Beskrivning

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.

Produktinformation

Utgivningsdatum:2008-12-10
Mått:185 x 235 x 23 mm
Vikt:814 g
Format:Häftad
Språk:Engelska
Antal sidor:379
Förlag:Stata Press
ISBN:9781597180474

Utforska kategorier

Affärsapplikationer inom Data och IT

Mer om författaren

Indiana University, Bloomington, USA

Recensioner i media

Select Guide Rating

Innehållsförteckning

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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Workflow of Data Analysis Using Stata

AvJ. Scott Long

Häftad, Engelska, 2008

950 kr

Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

Beskrivning

Produktinformation

Utgivningsdatum:2008-12-10
Mått:185 x 235 x 23 mm
Vikt:814 g
Format:Häftad
Språk:Engelska
Antal sidor:379
Förlag:Stata Press
ISBN:9781597180474

Utforska kategorier

Affärsapplikationer inom Data och IT

Mer om författaren

Indiana University, Bloomington, USA

Recensioner i media

Select Guide Rating

Innehållsförteckning

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.