Schedule

This schedule is subject to change. Check back here for the latest version.

Week 1

  • M 1/9 – Course Introduction
  • W 1/11 – Intro to Data
  • F 1/13 – Numerical Data (Reading: §1.1-1.3) – Reading #1 Due

Week 2

  • M 1/16 – MLK Day – No Class
  • W 1/18 – Categorical Data (Reading: §1.4) – Bookmark #1 Due, Reading #2 Due
  • F 1/20 – Data Visualization (Reading: None)

Week 3

Week 4

Week 5

  • M 2/6 – Random Variables (Reading: §2.5)
  • W 2/8 – Expected Values – Problem Set 2 Due
  • F 2/10 – Normal Distributions (Reading: §3.1) – Reading #8 Due

Week 6

  • M 2/13 – Normal Distributions – Reading #9 Due
  • W 2/15 – Midterm Exam 1
  • F 2/17 – Probability Plots (Reading: §3.2)

Week 7

Week 8

Week 9

  • M 3/5 – Spring Break – No Class
  • W 3/7 – Spring Break – No Class
  • F 3/9 – Spring Break – No Class

Week 10

  • M 3/12 – More Hypothesis Testing
  • W 3/14 – The Central Limit Theorem (Reading: §4.3.4-4.4) – Reading #13 Due
  • F 3/16 – Preview of Chapters 5 and 6

Week 11

Week 12

  • M 3/26 – More Least Squares – Application Project Proposals Due
  • W 3/28 – Midterm Exam 2
  • F 3/30 – Inference for Linear Regression (Reading: §7.3-7.4)

Week 13

Week 14

  • M 4/9 – Margins of Error; Infographics
  • W 4/11 – Hypothesis Tests for Proportions; Infographics – Problem Set 5 Due
  • F 4/13 – Small Samples, Population Mean (Reading: §6.1) – Reading #18 Due

Week 15

  • M 4/16 – Small Samples, Difference of Means (Reading: §6.2) – Reading #19 Due
  • W 4/18 – Special Topics & Course Evaluations – Problem Set 6 Due
  • F 4/20 – Machine Learning – Guest Speaker: Doug Fisher, Computer Science Department

Week 16

  • M 4/23 – Last Day of Class – Application Projects Due

Finals

  • F 4/27 – Alternate Final Exam, 12-2pm
  • Th 5/3 – Final Exam, 3-5pm

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