The links below will enable you to view the demo and assignment notebooks in your browser. If you’d like to edit and execute them yourself, follow these instructions to install the course software and download all the notebooks onto your own computer.

Introduction
W 01/24 Introduction
Lecture: Slides, Demo, Video
Reading: 1 		lab01
F 01/26 Cause and Effect
Lecture: Slides, Video
Reading: 2 		hw01
Data, Tables, and Graphs in Python
M 01/29 Tables
Lecture: Slides, Demo, Video
Reading: 5.0
W 01/31 Data Types
Lecture: Slides, Demo, Video
Reading: 3, 4 		lab02
F 02/02 Columns and Rows
Lecture: Slides, Demo, Video
Reading: 5.1, 5.2 		hw02
M 02/05 Census
Lecture: Slides, Demo, Video
Reading: 5.3, 5.4
W 02/07 Charts
Lecture: Slides, Demo, Video
Reading: 6.0, 6.1 		lab03
F 02/09 Histograms
Lecture: Slides, Demo, Video
Reading: 6.2, 6.3 		hw03
M 02/12 Functions
Lecture: Slides, Demo, Video
Reading: 7.0, 7.1
W 02/14 Groups
Lecture: Slides, Demo, Video
Reading: 7.2, 7.3 		lab04
F 02/16 Joins
Lecture: Slides, Demo, Video
Reading: 7.4, 7.5 		proj1
M 2/19 February Break (no class)
W 02/21 Table Examples
Lecture: Slides, Demo, Video
Distributions and Random Sampling
F 02/23 Control
Lecture: Slides, Demo, Video
Reading: 8.0, 8.1, 8.2
M 02/26 Probability
Lecture: Slides, Demo, Video
Reading: 8.3, 8.4
W 02/28 Sampling
Lecture: Slides, Demo, Video
Reading: 8.5, 9.0, 9.1, 9.2 		lab05
Thu 03/01 Prelim 1, 7:30pm, Goldwith Smith G76
F 03/02 No class: Snow Day
hw04
M 03/02 Estimation
Lecture: Slides, Demo, Video
Reading: 9.3
W 03/05 Simulation
Lecture: Slides, Demo, Video
lab06
Hypothesis Testing
F 03/09 Hypothesis Testing
Lecture: Slides, Demo, Video
Reading: 10, 10.1, 10.2 		hw05
M 03/12 Error Probabilities
Lecture: Slides, Demo, Video
Reading: 10.3 		proj2
W 03/14 Examples
Lecture: Slides, Demo, Video
Reading: 10.4
F 03/16 Confidence Intervals
Lecture: Slides, Demo, Video
Reading: 11.0, 11.1, 11.2
M 03/19 Interpreting Confidence
Lecture: Slides, Demo, Video
Reading: 11.3, 11.4
The Normal Distribution
W 03/21 Center and Spread
Lecture: Slides, Demo, Video
Reading: 12, 12.1, 12.2 		lab07
F 03/23 The Normal Distribution
Lecture: Slides, Demo, Video
Reading: 12.3, 12.4 		hw06
M 03/26 Sample Means
Lecture: Slides, Demo, Video
Reading: 12.5
W 03/28 Designing Experiments
Lecture: Slides, Demo, Video
Reading: 12.6
F 03/30 Sample Size Examples
Lecture: Slides, Demo, Video
M 04/02 Spring Break
W 04/04 Spring Break
F 04/06 Spring Break
Regression
M 04/09 Correlation
Lecture: Slides, Demo, Video
Reading: 13, 13.1
T 04/10 Prelim 2, 7:30pm, Kimball B11
W 04/11 Linear Regression
Lecture: Slides, Demo, Video
Reading: 13.2 		lab08
F 04/13 Least Squares
Lecture: Slides, Demo, Video
Reading: 13.3, 13.4 		hw07
M 04/16 Residuals
Lecture: Slides, Demo, Video
Reading: 13.5, 13.6
W 04/18 Regression Inference
Lecture: Slides, Demo, Video
Reading: 14 		lab09
Classification
F 04/20 Classification
Lecture: Slides, Demo, Video
Reading: 15, 15.1 		hw08
M 04/23 Nearest Neighbor
Lecture: Slides, Demo, Video
Reading: 15.2, 15.3, 15.4, 15.5 		proj3
W 04/25 Implementing Nearest Neighbor
Lecture: Slides, Demo, Video
F 04/27 Enhancing Nearest Neighbor
Lecture: Slides, Demo, Video
M 04/30 Multiple Regression
Lecture: Slides, Demo, Video
Reading: 15.6
Applications of Data Science
W 05/02 How Data Collection Influences How We Live, Work, and Interact—Prof. Karen Levy (Information Science)
Lecture: Slides, Video
F 05/04 Analyzing Data on a Cosmic Scale—Prof. Rachel Bean (Astronomy)
Lecture: Slides, Video
M 05/07 Privacy
Lecture: Slides, Demo, Video
W 05/09 What Next
Lecture: Slides, Video
M 05/14 Final Exam, 2:00 pm, Phillips 219