- Lecturer: Choong-Wan Woo, Ph.D. Assistant professor (GBME).
- Office: N-center, 86335
- Web: Cocoan lab
- E-mail: gbe3037.statprob@gmail.com
- Class: Mon 1:30-2:45, Wed 12:00-1:15 at 86102
- Office hours: Wed 10:00-12:00, you can book a time in advance through https://choongwanwoo.youcanbook.me
- Piazza link: here
You can download the class materials using the following command line.
$ git clone https://github.com/wanirepo/Stats_2019Spring.git
Once you clone the github repository, you can just type the following command to get the updated github repository.
$ git pull
Or you can download the repository as a zip file or you can also use GitHub Desktop. The class materials will be uploaded (e.g., lecture slides, assignments) before each class.
There is a good github tutorial: https://rogerdudler.github.io/git-guide/index.html
Data are everywhere. Data science already became a key element in many research and industrial areas. The primary aim of this course is to learn basic concepts and skills for data analysis, including concepts of random variables, sampling distributions, hypothesis testing, linear modeling, data visualization, etc., preparing you for your life after the graduation in this data-are-everywhere age. However, this is not the only aim of this class. Statistics goes beyond just data analysis, I believe. Statistics is a way of thinking and reasoning. It helps with scientific reasoning and critical thinking. Thus, I hope this class could provide you with some useful tips for scientific thinking and reasoning. Finally, I'd like to give you some hands-on experience of data analysis through flipped classroom.
This class uses a flipped classroom format, which is a new way of teaching and learning. Different from the traditional learning environment (passively listening to the lecture in the class and doing homework at home), in the flipped classroom, you will listen to the lecture at home and do homework and practices in the classroom. I personally experienced this format of learning during my PhD (for the Machine Learning class) and deeply enjoyed it. I found the flipped classroom helped students stay engaged and provided a good environment for hands-on experience. For these reasons, I have wanted to do the class with the flipped classroom format. Given that this year will be the first year of trying this new format, the class might not be perfect, but I promise to make the class better and better every year!
I will make and share the lecture videos every week. You should watch the lecture videos before you come to the class. This is crucial because the actual class will be conducted with the assumption that you already watch the video beforehand. If you don't watch the lectures, you might not be able to follow the class. I will help you by making the videos short! They will be short! I promise. Also I will ask some easy questions to students in a random order every class.
The videos will be in English (unless you really want them to be in Korean), but we can use Korean to ask questions and discuss.
We will use piazza as a platform for a class announcement, discussion, and questions.
Main textbook:
"Stats: Data and Models" by De Veaux, Velleman, and Bock
Supplements:
"Statistical Thinking for the 21st Century" by Russ Poldrack Link
"Seeing theory" Link
"The Seven Pillars of Statistical Wisdom" by Stephen M. Stigler Amazon Link
"History of Statistics Reading Group" (CMU) Link
Teaching how to use statistics packages or programming is not the main focus of this class. This class is more about statistical methods and theories. However, software packages and computer programming are actually essential in learning statistics. Therefore, I will provide two lectures about new software packages for statistical analysis, JAMOVI and JASP. They are brand-new and open-source tools for statistical analysis. In addition, I might use Matlab, Python, or R sometimes. You can download Matlab through SKKU. Python and R are open-source programming languages. I'm planning to open a new experiment class to teach how to use these tools (maybe next year). Therefore, stay tuned.
- Lada Kohoutová (ladakohoutova@gmail.com)
- Hongji Kim (redkim94@hanmail.net)
Absolute evaluation will be used for this course.
- Attendance (40%)
- Participation (including pop-questions) (35%)
- Midterm exam (10%)
- Final exam (15%)
| Week | Video lectures | Class | Chapters |
|---|---|---|---|
| Week 1 | |||
| 3/4 | V00: Class intro | Course overview | Survey |
| 3/6 | V01: Data | Cognitive errors! | Ch.1-2 |
| Week 2 | |||
| 3/11 | V02: Data visualization | Data visualization | Ch.3-4 |
| 3/13 | V03: Comparing distribution Note: I made both V03 and V04 into one video (accidentally). Watch only 14 mins of the video. |
Smoothing, re-expressing data | Ch.5 |
| Week 3 | |||
| 3/18 | V04: Normal model | P-P plot | Ch.6 |
| 3/20 | V05: Scatterplots and correlation Please complete Quiz |
Scatterplots and correlation | Ch.7 |
| Week 4 | |||
| 3/25 | V06: Linear regression Please complete Quiz |
Regression to the mean | Ch.8 |
| 3/27 | V07: More about regression, re-expressing data Please complete Quiz |
The effects of outlier on the regression | Ch.9-10 |
| Week 5 | |||
| 4/1 | V08: Sampling Please complete Quiz |
Design experiments! | Ch.12-13 |
| 4/3 | V10: Probability and bayes theorem Please complete Quiz |
Bayes theorem | Ch.14-15 |
| Week 6 | |||
| 4/8 | V11: Random variables Please complete Quiz |
Random variables | Ch.16 |
| 4/10 | V12: Probability models Please complete Quiz |
Probability models | Ch.17 |
| Week 7 | |||
| 4/15 | V13: JAMOVI V14: JASP |
JAMOVI and JASP practice in-class video Link for Data collection |
- |
| 4/17 | Review Please post your questions |
Q & A | - |
| Week 8 | |||
| 4/22, 24 | Mid-term | - | - |
| Week 9 | |||
| 4/29 | No Video today | L14: Sampling distribution, central limit theorem | Ch.18 |
| 5/1 | V15: Confidence interval for proportions Please complete Quiz |
Central limit theorem Link1 Link2 Wani research slide |
Ch.19 |
| Week 10 | |||
| 5/6 | No class (어린이날 대체공휴일) | ||
| 5/8 | V16: Hypothesis testing, P-values Please complete Quiz |
Let's watch V17 together V17: Inferences about means NHST and P-value |
Ch.21-22 |
| Week 11 | |||
| 5/13 | No class | - | - |
| 5/15 | V18: More about tests and intervals Please complete Quiz for V18 V19:Comparing groups Please complete Quiz for V19 |
Q&A, Confidence interval, T-test I | Ch.23-24 |
| Week 12 | |||
| 5/20 | V20: Paired t-test Please complete Quiz |
T-test II | Ch.25 |
| 5/22 | No class (festival; 자인전) | - | - |
| Week 13 | |||
| 5/27 | [V21] Comparing counts | lecture and Q&A | Ch.26 |
| 5/29 | V22: Review: Inferences about regression Please complete Quiz for V22 V23: Analysis of Variance (ANOVA) Please complete Quiz for V23 |
Watch the video lecture together and solve quiz together | Ch.27-28 |
| Week 14 | |||
| 6/3 | V24: Multifactor ANOVA Please complete Quiz |
TBD (led by Lada) | Ch.29 |
| 6/5 | V25: Multiple regression Quiz for V25 V26: Multiple regression wisdom Quiz for V26 |
Review | Ch.30-31 |
| Week 15 | |||
| 6/10 | Review (led by Hongji) Link for submitting the review questions (please complete the submission until Friday 6PM) |
- | - |
| 6/12 | No class | - | - |
| Week 16 | |||
| 6/17, 19 | Final | - | - |
Note.
I will be out of town on 5/13, 6/10, 6/12 for conferences. Weekly plan described above can be adjusted as our class develops.