11 Week 11

  • Dates: 11/01/2021 - 11/07/2021

11.1 Lectures

Topic Video Mirror Notes
11.1 Plotting with Matplotlib.pyplot [ClassTranscribe] [YouTube] [11.1]
11.2 Plotting with seaborn [ClassTranscribe] [YouTube] [11.2]
11.3 Intro to Plotly - Plotly Express [ClassTranscribe] [YouTube] [11.3]

11.2 Discussion/Lab

  • No lab

11.3 Homework

  • [Homework 09] - Due: Friday 11/12/2021

11.4 Deadlines

  • Lab 08 - 11:59 PM Tuesday 11/02/2021
  • HW 08 - 11:59 PM Friday 11/05/2021 (80% - 11:59 PM Sunday 11/07/2021)

11.5 Upcoming - Exam 2

11.5.1 Location, Date, and Time

  • Time: 7:00 PM - 8:50 PM Tuesday 11/09/2021
    • You will be given 110 minutes to complete the exam.
  • Format: PrairieLearn exam.
  • Proctor Service: Course staff proctoring through Zoom.
  • Conflict exams:
    • Option 1: Tuesday 11/09/2021, 8:00 PM - 9:50 PM
    • Option 2: Wednesday 11/10/2021, 8:00 AM - 9:50 AM
  • To take the conflict exam, please submit a conflict request here by 7:00 PM Monday 11/08/2021. After that, I will not approve any conflict exam request.

11.5.2 Exam Content

All content from week 6 up until the end of week 10, but the questions might require knowledge and skills from previous weeks as well.

  • 6.1 Intro to Git & GitHub
  • 6.2 Git Branches
  • 7.1 pandas: Series
  • 7.2 pandas: DataFrame
  • 7.3 pandas: Essential Functionality
  • 7.4 pandas: Summarizing and Computing Descriptive Statistics
  • 8.1 pandas: Reading & Writing Data
  • 8.2 pandas: Data Cleaning
  • 8.3 pandas: Data Transformation
  • 9.1 pandas: Data Wrangling
  • 9.2 pandas: GroupBy Mechanics
  • 10.1 Data Aggregation
  • 10.2 String Manipulation
  • 10.3 Regular Expressions
  • Lab 05
  • Lab 06
  • Lab 07
  • Lab 08

11.5.3 Materials Provided

  • No material will be provided.

11.5.4 Materials Needed

  • Laptop with high-speed internet.
  • Phone with camera or other device with camera used for proctoring.

11.5.5 Materials Allowed

  • 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.

11.5.6 Exam Format

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.

11.5.7 Academic Integrity

In short, don’t cheat. Any violation will be punished as harshly as possible.