$$
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$$
Introduction (Week-1)
Math 183 • Statistical Methods • Spring 2026
Course Information
![]()
ucsd-math183.github.io/sp26
- Lectures. Tue/Thu. 3:30–4:50 PM
- Discussions. Thursday Evenings
- Midterm. Thu, Apr 30th, 2026
- Final. Mon, Jun 8th, 2026
Tips on succeeding in this course
Study Habits and Strategies
- Regular Review vs Cramming:
- Benefits of spaced repetition and active recall
- Long-term retention and understanding
- Active Participation:
- Engaging in class discussions
- Collaborative learning and group studies
- Look at the course policy here
Seeking Help and Utilizing Office Hours
- Recognizing the Need for Help:
- It’s okay to ask questions!
- Encouraging a culture of curiosity and inquiry
- Office Hours and TA Sessions:
- Make the most out of one-on-one interactions
- Collaborating and brainstorming with peers
- Accommodations:
- Commitment to creating an inclusive learning environment
- Students with documented disabilities can request necessary accommodations
- Processes in place for confidential discussions and implementations
Academic Integrity
- I’d much rather you ask for help from me or the TAs or discuss with your peers
- Please acknowledge your sources (if you use any)
FAQs
- How many homeworks will there be?
- Expect about 7-8 homeworks
- Will the lectures be podcast-ed?
- Yes, starting from Week-1 they will be uploaded automatically
- Are we allowed cheatsheets on the exam
- Yes. 1 A4/Letter sheet. Both sides are okay. It doesn’t have to be handwritten
- Will there be make-up exams
- No. There will be no make-up exams. However, there are two grading schemes in the event you don’t take your midterm
- Can I submit my assignment late?
- No.
- Seriously?
- Yes. But your lowest score will be dropped! 🙂
- I sent you an email and didn’t get a response!
- Please include “[Math 183]” in your subject and CC your TAs
Why Statistics?
- It’s a discipline centered around data.
- Collect: Gathering accurate and representative data for study.
- Describe: Summarizing data to grasp its main characteristics.
- Visualize: Representing data graphically for better understanding.
- Analyze: Extracting meaningful insights from data to make informed decisions.
- Empowered Decision Making:
- Proactive Choices: Leveraging data to make forward-thinking decisions.
- Critical Evaluation: Evaluating and scrutinizing decisions others make based on the data.
Examples
![]()
Examples
![]()
A Brief History of Statistics
![]()
