/STAT5206_Fall_2022

Statistical Computing and Introduction to Data Science @ Columbia Stats

Statistical Computing and Introduction to Data Science

STAT5206 - Fall 2022

Learning outcomes

  • Understand basic programming
    • Manipulate data with different structures
    • Control flow
    • Functions
  • Explore data via visualization
  • Study statistical concepts via simulations
  • Automate tasks with programming
  • Understand basic optimization

Prerequisites

  • An introductory statistics class
    • Basic probability distributions (e.g. Gaussian, binomial distributions and their likelihoods)
    • Basic hypothesis testing (e.g. t-test)
    • Summary statistics
    • Histograms, boxplots, etc
  • Multivariate calculus
    • Derivatives and functions
  • Matrix operations and inverses of matrices
  • You should be at least co-enrolled in a modeling class like regression

Textbooks and references

Timeline

Date Topic Reference Due
2022-09-09 - Introduction
- Python 101-1 (Variable 1, Function, Package)
- Numpy 1		 - PCN Chapter 1, 2, 3, 4, 6, 8, 11
- PPSC Chapter 1, 2
- PDSH Chapter 2
2022-09-16 - Python 101-2 (Variable 2, Loop)
- Numpy 2
- OLS
- uni/bi-gram		 - PCN Chapter 5, 7, 11
2022-09-23 - Python 101-3 (if/else, File I/O, Exception handling)
- AB testing		 - PCN Chapter 9, 10 - HW0 (Sep 24th, 2:00 PM, NOT-GRADED)
- HW1 (Sep 25th, 11:59 PM)
2022-09-30 - Pandas 1 (DataFrame, Grouping)
- COVID-19		 - PCN Chapter 12, 14
2022-10-07 - Pandas 2 (Merge, Timestamp)
- Visualization (matplotlib, seaborn)		 - PCN Chapter 12, 15, 16
- Set up your jupyter notebook environment with the command line		 - HW2 (Oct 9th, 11:59 PM)
2022-10-14 - Regular expression
- NYTimes		 - PCN Chapter 13
2022-10-21 - Interacting with APIs
- Twitter		 - PCN Chapter 17 - HW3 (Oct 25th, 11:59PM)
2022-10-28 Midterm (in class)
2022-11-04 - Midterm review
- SQL		 - PCN Chapter 20
2022-11-11 - Linear Model (Feature Engineering, Data Splitting, Cross-validation)
- Medical Insurance		 - PCN Chapter 18
- PDSH Chapter 5
2022-11-18 - Optimization (Objective functions, Regularization) - PCN Chapter 19 - HW4 (Nov 20th, 11:59 PM)
2022-11-25 Thanksgiving NO CLASS
2022-12-02 Amazing guest lecture - HW5 (Dec 4th, 11:59 PM)
2022-12-09 - Review
2022-12-16 Final at 7:10 PM

Logistics

Class time: F 10:10am - 12:40pm, Location: 402 Chandler

Teaching Team

Yongchan Kwon (yk3012)

  • Office Hours: Every Tuesday 2:30 PM - 4:00 PM and Every Wednesday: 7 PM - 8:30 PM at 901-C, School of Social Work.

Maria-Cristiana Girjau (mg4345)

  • Office hours: Every Thursday 9:00AM - 11:00 AM at the 10th floor lounge, School of Social Work.

Grading

If your final grade is in [93-97), you will earn at least an A, [90-93) will earn at least an A-, [87-90) will earn at least a B+, etc. A grading curves may occur depending on the class performance but I will not curve downwards. I will not give out A+ for this class.

- Homeworks (25%)

  • Late homeworks will receive 0 credit
  • No make-up homeworks will be granted even if you registered late to the class
  • If you want to learn how to set up Jupyter Notebooks with R, follow these instructions
  • Please read these important things related to submitting homeworks on Ed

- Exams (65%)

  • Midterms (30%)
  • Final (35%)

- Participation (10%)

  • In class participation
  • Online question posting (non-private) and answers are all ways to achieve this
  • I will reach out after the midterm if you are at risk of missing some points here.
Exam accomodations

In order to receive disability-related academic accommodations for this course, students must first be registered with their school Disability Services (DS) office. Detailed information is available online for both the Columbia and Barnard registration processes.

Refer to the appropriate website for information regarding deadlines, disability documentation requirements, and drop-in hours(Columbia)/intake session (Barnard).

For this course, students are not required to have testing forms or accommodation letters signed by faculty. However, students must do the following:

· The Instructor section of the form has already been completed and does not need to be signed by the professor.

· The student must complete the Student section of the form and submit the form to Disability Services.

· Master forms are available in the Disability Services office or online: https://health.columbia.edu/services/testing-accommodations

Expectations

  • Take chances!
    • Break the code in lecture
  • Give feedback in office hours or e-mail, don't waste your time if you think a topic is not helpful
  • Participate and ask questions, this is not easy!
    • In class: forecast what should be done, compare with what is happening, then summarize the difference.
    • Online: describe what you observe, describe what you expect, communicate clearly.
    • To each other: summarize the conversation to ensure you're listening and think constructively before criticizing.
  • THE MOST IMPORTANT Academic honesty: https://www.cs.columbia.edu/education/honesty/

Acknowledgement

A lot of these materials are based off the materials from Prof. Wayne Tai Lee's STAT5206 homepage.