Learn basic probability and statistics theorems and apply them to practical problems.
In the week right after the midterm exam, we will focus on applying probability theory and statistics to practical problems such as engineering-related problems, machine learning, data science, etc.

Calculus 1 and 2.

- Homework (15%), Quiz (10%), Midterm (35%), Final (35%) + Attendance (5%)
- There will be a total of 8~10 homework assignments during this semester.
- The schedule of quizzes is not fixed. I can ask you a simple question during a lecture anytime. Your submission for each quiz will also count as attendance.
- Homework will be assigned on Monday, and it is supposed to be submitted within 7 days (11:55 pm on the following Monday).
- The first homework will be assigned on 9th September 2024.
- No late homework will be accepted!
- No make-up exams!

Week 1: Introduction, Probability (Ch 1.1 – 1.9, 2.1 – 2.8), Random variables (Ch 3.1 – 3.3)
Week 2: Random variables (Ch 3.1 – 3.3)
Week 3: Joint Prob Dist (Chap 3.4), Mathematical expectation (Ch 4.1 – 4.5)
Week 4: Discrete probability distributions (Ch 5.1 – 5.3)
Week 5: Discrete probability distributions (Ch 5.4 – 5.7)
Week 6: Continuous probability distributions (Ch 6.1 – 6.5)
Week 7: Continuous probability distributions (Ch 6.6 – 6.9), Functions of random variables (Ch 7.1 – 7.3)
Week 8: Midterm (10/21/2024, 20:00--23:00),
Week 9: Application of probability theory
Week 10: Sampling distributions (Ch 8.1 – 8.5)
Week 11 : Sampling distributions, One and two sample estimation (Ch 8.6--8.7, Ch 9.1 – 9.5)
Week 12 : One and two sample tests (Ch 9.6--9.15, 10.1 – 10.4)
Week 13: One and two sample tests (Ch 10.4 – 10.17), Simple linear regression (Ch 11.1 – 11.3)
Week 14: Simple linear regression (Ch 11.4 – 11.13)
Week 15: Application of statistics
Week 16: Final (12/16/2024, 20:00--23:00, depending on the schedule of the Calculus exam, the exam can be held on 12/17/2024 Tuesday),

1. About coding skills: Some homework problems require use of a programming language. No worries, those are not complicated. You can use any programming language such as Python, Excel, Matlab, Mathematica, R, etc. If you have no experience with such programs, TAs will teach you simple coding with Python. For sharing TA's codes with you, TA discussions will be held remotely using Zoom. During the first TA discussion, they will also show you how to install Python.

The problems requiring a programming language will be very simple, so you are not expected to learn advanced coding skills. I believe self-learning is sufficient. Additionally, you can use the TA sessions as TAs will cover coding problems in more detail. Only homework assignments require coding; exams and quizzes do not.

2. About quizzes: Your lowest quiz score will not be counted into your grade because you may miss a lecture due to illness or other unavoidable issues.

3. Please bring a small piece of paper so that you can submit a quiz at any time.

Consider the following question: How can we derive meaningful principles and analyses of the underlying model from given numerical data sets?
To answer the questions, we will learn basic probability theory first. And then we will study basic and advanced statistical methods to handle data and to test hypotheses we are interested in about the underlying model or population.
We will also see how the tools we learned can be applied to problems in engineering, AI, and other scientific areas.