Lecture 0 Notes

Goals

• Have a high-level view of what Data Science is about and what data scientists do

• Begin thinking about how to ask questions that can be answered with data.

• Understand what is meant by a few properties of data:

  • Structure vs unstructured
  • Numerical vs categorical
  • Big vs small

Intro and Logistics

• [slides] Welcome; about me
• [slides] Plan for today
• [slides / webpage] Logistics
  • Webpage/syllabus
    • Schedule table (flexibility)
    • Major assessment items / cadence

What is data science? What is data?

• [ws/wb] What is data science? Student suggestions
  • my take: The process and/or study of extracting insights from data.
  • premise: “Data is not information is not unsderstanding is not wisdom” - Clifford Stoll
  • Tools: CS, Stats, Domain expertise
  • Practitioners: CS, Stats, Business
• [ws/wb] What do data scientists do? Student suggestions
  • answer questions
  • discover patterns, trends, insights
  • make predictions (classification, regression)
• [ws/wb] What is data? Student suggestions
  • Properties of data
    • structured/unstructured
    • numerical/categorical
    • big/small
  • Types of Structured data
    • table/matrix (this is our jam in this class)
      • example: course roster / gradebook
    • tree
      • who works for whom at WWU? (Org chart)
    • graph
      • who’s friends with whom? (Facebook)
    • stream/time series
      • stock values; median home prices; consumer price index; hourly temperature