These are my course notes for Understanding and Visualizing Data course 1 from Coursera Statistics with Python specialization.

Starting in July 2019.
Patricia Schuster, University of Michigan

• Week 1 notes
  • Where do data come from? organic/process data, designed data collection
  • i.i.d.: independent, identically distributed
  • Variable types: quantitative (continuous, discrete), categorical (ordinal, nominal)
  • Study design: Exploratory vs. confirmatory, comparative vs. non-comparative, observational vs. experiment, power and bias

• Week 2 notes
  • Categorical data: tables, bar charts, pie charts
  • Quantitative data: histogram, numerical summaries, standard score, box plots
  • Tables, histograms, and boxplots in Python
  • Examples with the tips_data dataset from seaborn

• Week 3 notes
  • Multivariate data
  • Associations with multivariate quantitative data
  • Pizza study design assignment
  • Quiz