Introduction To Statistics

Statistics gives us the language to interview, understand, and use data. We’ll give you the basic literacy to navigate your later courses and hopefully see the world a bit differently afterwards.

Prerequisites

• Algebra that uses the summation sign with subscripts

Textbooks / References

• Our main text: SticiGui from UC Berkeley by Philip Stark
• what other sections are using: Stats: Data and Models by De Veaux, Velleman, and Bock

Timeline

I reserve the right to change the ordering and the content for the course throughout the semester.

Date	Topic	Reference	Due
2023-01-17	Hello and overview	Chapter 3 - Types of variables
2023-01-19	Observing data - graphs	Chapter 3
2023-01-24	Observing data - statistics	Chapter 4	Homework 1 - Prerequisites
2023-01-26	Properties of statistics and extending to 2 variables	Chapter 4 and Chapter 5
2023-01-31	Regression as a summary statistic	Chapter 8, Chapter 5, Chapter 7, and Chapter 9
2023-02-02	Regression as a summary statistic	Chapter 8, Chapter 5, Chapter 7, and Chapter 9	Homework 2
2023-02-07	Fallacies and paradoxes	Regression Effect, Ecological correlation, Confounding
2023-02-09	Where data comes from - survey and sampling	Chapter 24
2023-02-14	Midterm review		Homework 3
2023-02-16	Midterm 1
2023-02-21	Midterm debrief
2023-02-23	Where data comes from - experiments
2023-02-28	Sampling to probability - counting	Chapter 12
2023-03-02	Probability - fundamentals	Venn diagrams and sets - Chapter 14, Axioms - Chapter 17
2023-03-07	Probability - the box model and modeling data as random variables	Chapter 19 and a little on Chapter 21 and Chapter 22	Homework 4
2023-03-09	Probability - expectations and standard error	Chapter 21 and Chapter 22
2023-03-14	Spring Recess
2023-03-16	Spring Recess
2023-03-21	Central Limit theorem	Chapter 23
2023-03-23	Probability buffer		Homework 5
2023-03-28	Midterm Review
2023-03-30	Midterm 2
2023-04-04	Midterm 2 debrief
2023-04-06	Confidence intervals	Chapter 26
2023-04-11	Hypothesis testing	Chapter 27
2023-04-13	Permutation tests and other tests		Chapter 31
2023-04-18	Statistical Power	Chapter 27	Homework 6
2023-04-20	Papers - Psychology/Econ
2023-04-25	Papers - Government/Industry
2023-04-27	What we know and don’t know		Homework 7
TBD	Measure understanding	Final Exam	You!

Logistics

Lectures: TuTh 10:10am - 11:25am, 402 Chandler

Where to ask questions

• Instructor - Wayne Tai Lee (wtl2109)
  • OH: 324 Uris on Tu 1-3pm and Wed 9:30-11:30am
• TA - Ling Chen (lc3521)
  • OH: School of Social Works 10th Floor Lounge, M 3-5pm
• Help room
  • Hours and Location
• Online Discussion on Ed:
  • Login through Canvas
  • The TA + grader will only check the online discussion for 30 minutes each weekday. Do not expect an immediate response so please start your work early.

Grading

If your final grade is in [93-100], 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 may not give out A+’s in this class. If you can pass the final exam, you cannot fail the class (passing is not determined by a percentage but by a close reading from the instructor).

- Homeworks (30%)

• Late homeworks will receive 0 credit.
• Your lowest homework will be dropped. This is mostly to accommodate people enrolling in the course late.
• Extensions will only be given in the event of a emergency.
• These should be submitted on Canvas.
• Each homework has the same weight.

  - Exams (65%)

• You can request to take the exam earlier than scheduled, but this request should come at least a week before the exam takes place.
• Having too many exams is not a reason to change your exam time.

  - Participation (5%)

• Instead of attendance, in class activities, recorded through Canvas, is how we’ll grade this.
• If you surpass 75% here, you’ll receive the full credit for participation, otherwise you’ll receive whatever percentage you earned.