1. Learning goals

For you:

  • get a first (or second) look at tools;
  • gain some experience in the basic command line;
  • get 80% of way to a complete analysis of some data;
  • introduction to philosophy and perspective of data analysis in science;

2. Safe space and code of conduct

This is intended to be a safe and friendly place for learning!

Please see the Software Carpentry workshop Code of Conduct: http://software-carpentry.org/conduct.html

In particular, please ask questions, because I guarantee you that your question will help others!

3. Instructor introductions

Harriet Alexander - postdoc at UC Davis.

Titus Brown - prof at UC Davis in the School of Vet Med.

4. Amazon and cloud computing - why?!

  • simplifies software installation;
  • can be used for bigger analyses quite easily;
  • good for “burst” capacity (just got a data set!)
  • accessible everywhere;

5. Sticky notes and how they work... + Minute Cards

Basic rules:

  • no sticky note - “working on it”
  • green sticky note - “all is well”
  • red sticky note - “need help!”

Place the sticky notes where we can see them from the back of the room – e.g. on the back of your laptop.

At the end of each session (coffee break, lunch, end of day) please write down on an index card one thing you learned and one thing you’re still confused about.

Next: n-overview

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