Week Date Lecture Reading Discussion/Lab Homework Project
Introduction Wed
8/24
Introduction (slides) (video) 1.1
1.2
1.3
Intro to Notebooks/Python (data8)
(ds8) (due whenever)
Fri
8/26
Cause and Effect (slides) (video) Chapter 2 HW01 (data8) (ds8)
(due 9/1)
Python
Basics
Mon
8/29
Expressions (slides) (video) Chapter 3
Wed
8/31
Sequences (slides) (notebook) (video) Chapter 4 Data Types and Sequences (data 8) (ds8)
Visualization:
Graphs
and
Tables
Fri
9/2
Tables Part 1 (slides) (video) 5
5.1
HW02 (data8) (ds8)
(due 9/8)
Mon
9/5
No Class: Labor day
Wed
9/7
Tables Part 2 (slides) (video) 5.2
5.3
5.4
Arrays and Tables (data8) (ds8)
Fri
9/9
Graphs (slides) (video) 6
6.1
HW03 (data8) (ds8)
(due 9/15)
Mon
9/12
Graphs Part II (slides) (video) 6.2
6.3
Wed
9/14
Functions and Tables (slides) (video) 7
7.1
Functions and Histograms (data8) (ds8)
Fri
9/16
Functions and Tables Part 2 (slides) (video) 7.2
7.3
HW04 (data8) (ds8)
(due 9/22)
Mon
9/19
Functions and Tables Part 3 (slides) (video) 7.4
7.5
Distributions
and
Random
Sampling
Wed
9/21
Iteration (slides) (video) 8
8.1
Project 1 Project 1 (due 10/4)
Fri
9/23
Randomness (slides) (video) 8.2
8.3
Mon
9/26
Sampling (slides) (video) 8.4
8.5
Wed
9/28
Empirical Distribution of a Sample (slides) (video) 9
9.1
9.2
Project 1 Checkpoint (due 9/27)
Fri
9/30
Empirical Distribution of a Statistic (slides) (video) 9.3 HW05 (data8) (ds8)
(due 10/6)
Testing
Statistical
Hypothesis
Mon
10/3
Total Variation (slides) (video) 10.1
Wed
10/5
Hypothesis Testing (slides) (video) 10.2 Statistics in Sampling (data8) (ds8)
Fri
10/7
Error Probabilities (slides) (video) 10.3 HW06 (data8) (ds8) (due 10/13)
Mon
10/10
Examples (slides) (video) 10.4
Midterm Wed
10/12
Midterm Review (slides) (video) Midterm Review
Fri
10/14
Midterm
Estimation Mon
10/17
Bootstrap Confidence Intervals (slides) (video) 11
11.1
11.2
Wed
10/19
Interpreting CIs (slides) (video) 11.3 The Bootstrap (data8)(ds8)
Fri
10/21
CI Testing (slides) (video) 11.4 HW07 (data8) (ds8) (due 10/27)
Why
the
Mean
Matters
Mon
10/24
Averages and Standard Deviation (slides) (video) 12
12.1
12.2
Wed
10/26
SD and Normal Curve (slides) (video) 12.3
12.4
Project 2 (data8) (ds8) Project 2 (due 11/8 at 7pm, Checkpoint due 11/1 at 7pm)
Fri
10/28
Variability of the Sample Mean (slides) (video) 12.5
12.6
HW08 (data8) (ds8) (due 11/3)
Prediction Mon
10/31
Scatter Plots and Correlation (slides) (video) 13
13.1
Wed
11/2
Regression (slides) (video) 13.2 Introduction to Regression (ds8) Project 2 Checkpoint (due 11/1 at 7pm)
Fri
11/4
Least Squares (slides) (video) 13.3 HW09 (data8) (ds8) (due 11/10)
Assessing
Predictions
and
Models
Mon
11/7
Regression Inference I (slides) (video) 13.4
13.5
13.6
14
14.1
Wed
11/9
Regression Inference II (slides) (video) 14.2
14.3
Regression Inference (ds8)
Fri
11/11
Holiday: No School HW10 (data8) (ds8) (due 11/17)
Predicting
Categories
Mon
11/14
Classification I (slides) (video) 15
15.1
15.2
Wed
11/16
Classification II (slides) (video) 15.3
15.4
15.5
Classification and Project 3 (data8) (ds8) Project 3 (due 11/29 at 7pm, checkpoint due 11/22 at 7pm)
Comparison,
Causality
and
Decisions
Fri
11/18
Comparing Samples I (slides) (video) 16
16.1
HW11 (data8) (ds8) (due 11/28)
Mon
11/21
Comparing Samples II (slides) (video) 16.2
Wed
11/23
Thanksgiving: No School
Fri
11/25
Thanksgiving: No School
Mon
11/28
Causality (slides) (video) 16.3
Wed
11/30
Bayes and decisions (slides) (video) 17
17.1
17.2
Bayes Lab
Fri
12/2
Conclusion (slides) (video) HW12 (optional practice problems)