- Dates: 09/20/2021 - 09/26/2021
|5.1 NumPy: Mathematical & Statistical Methods||[ClassTranscribe]||[YouTube]||[5.1]|
|5.2 NumPy Application: Random Walks||[ClassTranscribe]||[YouTube]||[5.2]|
- [Homework 04] - Due: Friday 10/01/2021
- Lab 04 - 11:59 PM Tuesday 09/21/2021
- HW 03 - 11:59 PM Friday 09/24/2021 (80% - 11:59 PM Sunday 09/26/2021)
Time: 7:00 PM - 8:50 PM Tuesday 09/28/2021.
- You will be given 110 minutes to complete the exam.
- Format: PrairieLearn exam.
- Proctor Service: Course staff proctoring through Zoom.
- Option 1: Tuesday 09/28/2021, 8:00 PM - 9:50 PM
- Option 2: Wednesday 09/29/2021, 8:00 AM - 9:50 AM
- To take the conflict exam, please submit a conflict request here by 7:00 PM Monday 09/27/2021. After that, I will not approve any conflict exam request.
- Note that submitting a conflict request does NOT guarantee approval. You will receive an email with the decision (approval/denial) within 1 business day of submission.
All content from week 1 up until the end of week 5.
- Lab 01
- 1.3 Basics of Programming
- 1.4 Data Types
- 2.1 Control Flow
- 2.2 Function
- Lab 02
- 2.3 Tuple
- 3.1 List
- 3.2 Dictionary
- Lab 03
- 3.3 Errors & Exception Handling
- 4.1 NumPy Basics: Part 1
- 4.2 NumPy Basics: Part 2
- Lab 04
- 5.1 NumPy: Linear Algebra
- 5.2 NumPy: Mathematical & Statistical Methods
- 5.3 NumPy Application: Random Walks
- Laptop with high-speed internet.
- Phone with camera or other device with camera used for proctoring.
- Materials on the course website at https://stat430.hknguyen.org.
- The use of Jupyter Notebook on your local computer.
- Only blank new notebooks will be allowed.
The exam consists of 10 questions:
- 4 multiple-choice questions
- 6 coding questions
The point structure for each question type is described as followed:
- For multiple-choice questions, you will get 2 attempts: 1st attempt with 100% credit, 2nd attempt with 50% credit.
- For the coding questions, you will get 10 attempts for each question with full credits. After those 10 attempts, you will get 5 more attempts with 75% credit.
- So, it is highly recommended that you first work on the question in Jupyter Notebook and test it before submitting your answer to PL.