Schedule and Material
| Week | Day | Date | Topic | Book Sections* | Slides*** | Data | Supplementary Materials |
|---|---|---|---|---|---|---|---|
| 1 | M | Jan 12 | Intro. & Basic Stat. & Prob. Review 01 | Syl., 1.2, 1.4, 1.5 | slides podcast** video** |
data | - Video: The NBA Data Scientist - Video: Hans Rosling’s 200 Countries, 200 Years - IMS: Introduction to data |
| 1 | W | Jan 14 | Basic Stat. & Prob. Review 02 | 1.8, 3.3 (omit Chebyshev), 3.4, 3.5 | slides podcast** video** |
data | - Video: Data Basics - Video: Summarizing and Graphing Numerical Data - Video: Exploring Categorical Data - IMS: Exploratory data analysis |
| 1 | F | Jan 16 | Basic Stat. & Prob. Review 03 | 6.2, t Dist. Supplement | slides podcast** video** |
. | - Video: Normal Distribution |
| 2 | S | Jan 18 | Homework 01 Due date | Basic Stat. & Prob. Review | . | . | . |
| 2 | M | Jan 19 | MARTIN LUTHER KING JR. DAY | — | . | . | . |
| 2 | W | Jan 21 | Int. Est. Review | 8.1, 8.2, 8.3, 8.4 | slides podcast** video** |
. | - Video: Point Estimates - Video: Confidence Intervals - Video: t-distribution |
| 2 | F | Jan 23 | Hyp. Testing Review 01 | 9.1, 9.2, 9.4, 9.5 | slides podcast** video** |
. | - Video: Hypothesis Testing Fundamentals |
| 2 | S | Jan 25 | Homework 02 Due date | Basic Stat. & Prob. Review | . | . | . |
| 3 | M | Jan 26 | Hyp. Testing Review 02 | 11.1, 11.2 | slides podcast** video** |
data | - Nature: Statisticians issue warning over misuse of P-values |
| 3 | W | Jan 28 | Quiz 1 | Review Material | . | . | . |
| 3 | F | Jan 30 | Analysis of Variance | 13.1, 13.2 | slides podcast** video** |
data | - Video: ANOVA Introduction - Video: Conditions for ANOVA - Video: Multiple comparisons |
| 3 | S | Feb 1 | Homework 02 Due date | Int. Est. & Hyp. Testing Review | . | . | . |
| 4 | M | Feb 2 | Simple Regression | 14.1 | slides podcast** video** |
data | - Video: Line Fitting & Correlation |
| 4 | W | Feb 4 | Simple Regression | 14.2, 14.3 | slides podcast** video** |
. | . |
| 4 | F | Feb 6 | Simple Regression | 14.4, 14.5 | slides podcast** video** |
. | . |
| 5 | M | Feb 9 | Simple Regression | 14.6, 14.7 | slides podcast** video** |
. | . |
| 5 | W | Feb 11 | Simple Regression | 14.8 | slides podcast** video** |
. | . |
| 5 | F | Feb 13 | Simple Regression | 14.9 | slides podcast** video** |
. | . |
| 5 | S | Feb 15 | Homework 03 Due date | Simple Regression | . | . | . |
| 6 | M | Feb 16 | Midterm 1 Review | Analysis of Variance & Simple Regression | . | . | . |
| 6 | W | Feb 18 | Midterm 1 Review | Analysis of Variance & Simple Regression | . | . | . |
| 6 | W | Feb 19 | Midterm 1 (TBD pm–TBD pm, TBD) | Analysis of Variance & Simple Regression | . | . | . |
| 6 | W | Feb 20 | No Class | . | . | . | . |
| 7 | F | Feb 23 | Multiple Regression | 15.1, 15.2, 15.3 | slides podcast** video** |
data | - Video: Introduction to Multiple Regression |
| 7 | W | Feb 25 | Multiple Regression | 15.4 | slides podcast** video** |
. | . |
| 7 | F | Feb 27 | Multiple Regression | 15.5 | slides podcast** video** |
. | . |
| 8 | M | Mar 2 | Multiple Regression | 15.6 | slides podcast** video** |
. | . |
| 8 | W | Mar 4 | Multiple Regression | 15.7 | slides podcast** video** |
. | . |
| 8 | S | Mar 8 | Homework 04 Due date | Multiple Regression, Pt. 1 | . | . | . |
| 9 | M | Mar 9 | Model Building | 16.1, 16.2 | slides podcast** video** |
data | - Video: Model Selection in Multiple Regression |
| 9 | W | Mar 11 | Quiz 2 | Multiple Regression | . | . | . |
| 9 | F | Mar 13 | Model Building | 16.3, 16.4 | slides podcast** video** |
. | . |
| 10 | M | Mar 16 | Spring Break (No class) | — | . | . | . |
| 10 | W | Mar 18 | Spring Break (No class) | — | . | . | . |
| 10 | F | Mar 20 | Spring Break (No class) | — | . | . | . |
| 10 | S | Mar 22 | Homework 05 Due date | Multiple Regression, Pt. 2 | . | . | . |
| 11 | M | Mar 23 | Logistic Regression | Supplement in Brightspace & Slides | slides podcast** video** |
. | - Video: Basic Ideas of Logistic Regression |
| 11 | W | Mar 25 | Logistic Regression | Supplement in Brightspace & Slides | slides podcast** video** |
. | . |
| 11 | F | Mar 27 | Logistic Regression | Supplement in Brightspace & Slides | slides podcast** video** |
. | . |
| 11 | S | Mar 29 | Homework 06 Due date | Logistic Regression | . | . | . |
| 12 | M | Mar 30 | Midterm 2 Review | Mult. Regr., Model Bldg., Log. Regr. | . | . | . |
| 12 | M | Apr 1 | Midterm 2 Review | Mult. Regr., Model Bldg., Log. Regr. | . | . | . |
| 12 | W | Apr 1 | Midterm 2 (TBD pm–TBD pm, TBD) | Mult. Regr., Model Bldg., Log. Regr. | . | . | . |
| 12 | F | Apr 3 | No Class | . | . | . | . |
| 13 | F | Apr 6 | Time Series | 17.1, 17.2, 17.3 | slides podcast** video** |
data | Video: Time Series Forecast Using Forecast Sheet in Excel |
| 13 | W | Apr 8 | Time Series | 17.4 | slides podcast** video** |
. | . |
| 13 | F | Apr 10 | Time Series | 17.5, 17.6 | slides podcast** video** |
. | . |
| 13 | S | Apr 12 | Homework 07 Due date | Time Series | . | . | . |
| 14 | M | Apr 13 | Quality Control | 19.1 | slides podcast** video** |
. | . |
| 14 | W | Apr 15 | Quiz 3 | Time Series | . | . | . |
| 14 | F | Apr 17 | Quality Control | 19.2, 19.3 | slides podcast** video** |
. | . |
| 15 | M | Apr 20 | Decision Analysis | 20.1 | slides podcast** video** |
. | - Video: Bayes theorem |
| 15 | W | Apr 22 | Decision Analysis | 20.2 | slides podcast** video** |
. | . |
| 15 | F | Apr 24 | Decision Analysis | 20.3, 20.4 | slides podcast** video** |
. | . |
| 15 | S | Apr 26 | Homework 08 Due date | Quality Control & Decision Analysis | . | . | . |
| 16 | M | Apr 27 | Final Exam Review | Cumulative | . | . | . |
| 16 | W | Apr 29 | Final Exam Review | Cumulative | . | . | . |
| 16 | F | May 1 | Final Exam Preparation | No class | . | . | . |
| 17 | — | TBD | Final Exam (TBD pm–TBD pm, TBD) | Cumulative | . | . | . |
*Section Numbers refer to sections in the course textbook.
** This material was generated with Google NotebookLM based on the slides prepared for the course.
*** Course material adapted from the textbook and previous course editions to better fit our curriculum. Thanks to Professor Jen Tang for guidance and for generously sharing the materials.