Lesson 20: Statistical Thinking in Python (Part 2)

April 4, 2018

Review:

  • Comparing Distributions
  • Term Project – let’s wait

Presentation:

  • More Data Visualization with Seaborn

Activity:

  • Use Seaborn “lmplot” to make a scatter plot + trendline with your real estate data
    • Make a basic scatter plot with trendline
      • x = Total Sq Ft, y = Selling Price
    • Make multiple plots (on the same graphic)
      • Group by neighborhood (hue=’Neighborhood’)

Assignment:

  • Complete Statistical Thinking in Python (Part 1)
  • Begin Statistical Thinking in Python (Part 2)

Justin

Justin Holman is CEO of Aftermarket Analytics, where he leads efforts to develop cutting edge sales forecasting and inventory optimization technology for the Automotive Aftermarket. Prior to joining Aftermarket Analytics, Justin managed corporate consulting for the Strategy & Analytics division at MapInfo Corporation, leading major projects for retail clients including The Home Depot, Darden Restaurants, Bridgestone-Firestone, Sainsbury’s and New York & Company. Before that, Justin served as Vice President of Software Development at LogicTools, now part of IBM's supply chain application software group. Justin holds a B.A. from Claremont McKenna College, a Ph.D. from the University of Oregon and an Executive Management certificate from Northwestern University's Kellogg School of Management.

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