Workflow of Data AnalysisContact and vita
July 7-11, 2014 | Instructor Scott Long | University of Michigan-Ann Arbor
Managing Statistical Research teaches you how to plan, organize, document, and execute sophisticated quantitative analyses regardless of the statistical methods used. The goal is to help you develop an workflow that allows you to work efficiently and accurately while producing results that are replicable. Topics include: 1) Planning your research. 2) Documenting your work. 3) Organizing, backing up, and archiving files. 4) Writing robust, effective programs for data analysis. 5) Using automation (basic programming methods) to work more accurately and efficiently. 6) Preparing data for analysis. 7) Systematically conducting statistical and graphical analyses. 8) Incorporating results into papers and presentations while maintaining their provenance. 9) Backing up your files. 10) Collaboration and data analysis. Lectures, exercises and applications are designed to help you develop a workflow for your own research.
Most of the class deals with strategies and procedures that are appropriate when working with any statistical package, such as SAS, Mplus, R, Stata, or SPSS. Some parts of the class show how to implement an effective workflow using Stata. However, these examples can readily be translated into other statistical packages. The most important things you will learn in this workshop are not specific commands, but rather principles and strategies that apply to any software.
Participants should bring a laptop along with copies of their research files (BE SURE TO HAVE BACKUPS OF THESE FILES!) Ideally, your laptop should have the statistical package you use installed. Each participant can have Stata installed on their laptop for use duing the class.
If you have questions, feel free to contact the instructor at jslong at indiana dot edu. For more information on the workflow of data analysis, check here. If you need further encouragement to take the class, check here.
This intensive workshop helps you develop a workflow for conducting complex statistical research. Workflow in data analysis is a framework for the entire research process: planning, organizing, and documenting your work; importing data; naming, labeling, documenting, creating, and verifying variables; conducting and presenting statistical and graphical analyses; and preserving your work. Each step is guided by the demands of producing reproducible and accurate results while working as efficiently as possible. While traditional classes in statistics deal with estimating and interpreting models, in "real world" data analyses this often involve less than ten percent of the total work. This class focuses on the other ninety percent. Developing an efficient workflow saves time, improves accuracy, and leads to replicable results. The workshop explores the following topics.
1, General principles that guide your research: replicability, accuracy, and efficiency.
2. Efficient methods for planning, organizing, documenting, executing, and preserving your work.
3. Tools that enhance and simplify your work: software, programming methods, organizational structure, and cyberinfrastructure.
4. Real world examples of what works and what does not in each stage of the process.
While many software tools are illustrated, Stata is use to illustrate an effective workflow, andthe course will refer to my The Workflow of Data Analysis Using Stata.
AutoHotkey: A freeware macro program.
TextWrangler: A highly recommended, freeware editor.
There are several things you can do to get ready for the class.
|© 2014 J. Scott Long|