Three steps to help your student interns become data savvy statisticans


With data standards rising in every industry, there’s a high demand for analysts and an unfortunate shortage of analytic talent. Many organizations are turning to student internships as a low-cost way to hire support, train potential new employees and provide real-world experience for students.

But, as Aleksandra Stein pointed out in her presentation at the Western Users of SAS Software (WUSS) conference in San Francisco this week: “Some students you can ‘buy off the shelf’ and implement right away. But some need help in performing all of the functions the organizations is looking to them to perform.” 

What these students learn in an academic setting is great, said Stein, but too often, the data they’re given to work on at school is not typical real-world data, i.e., these students are used to working with data that’s complete, balanced, correctly collected with analysis in mind and normal.  Ah, if only….

So, Stein suggests a CRASH COURSE in dealing with data.  Here are the top three things your young student analysts need to know:

Data structure: Data content: Data documentation:
  • Preparing
  • Restructuring
  • Mapping
  • Identifying keys
  • Data types
  • Formats
  • Sorting
  • Filtering
  • Merging
  • Counting
  • Summarizing
  • Identifying blanks
  • Internally
  • Externally
  • Log files
  • SAS Help

“These guys may not have ever had to write SAS code from scratch, and SAS Help is fantastic,” said Stein.

This crash course can take the form of a formal presentation, hard copy, soft copy, or an informal chat – “what you put into it is what you’re going to get out of it,” said Stein. “The time you invest to help them adjust to ‘real-world’ data will help you get your student interns to productivity much, much sooner.”

For more tips from Stein, read her full paper.


About Author

Anne-Lindsay Beall

Senior Editor

Anne-Lindsay Beall is a writer and editor for SAS. Since joining the company in 2000, Anne-Lindsay has edited print publications, Web sites, customer success stories, blogs and digital publications. She has a bachelor’s degree in English from the University of North Carolina at Chapel Hill and a master’s degree in English from North Carolina State University. You can find her on LinkedIn at:


  1. Pingback: Three steps to help your student interns become data savvy statisticans - Generation SAS

  2. All I can say is, "Hear! Hear!" When students complain to me that they only want to learn statistics and it is not their job to learn programming, merge files, re-code data or find errors, I am always tempted to ask them if the unicorns are blue on the planet they live on.

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