Week 4
Bayes’ Rule & EDA
Overview of Week 4
Day 6
- Random variables: Section 3.1
- Binomial distribution: Section 3.2
Day 7
- Normal distribution: Section 3.3
- Poisson distribution: Section 3.4
Slides & Recordings
- Pre-recorded lessons are on Echo Cloud (aka echo 360 or echo video).
| Day | Topic | Slides: html | Slides: pdf | Slides: web-page | Slides with notes | Recording Link | Duration | Code: qmd | Code: html |
|---|---|---|---|---|---|---|---|---|---|
| Calculating probabilities in R | |||||||||
| 6 | Random Variables (3.1.1-3.1.3) | Day 6: slides 1-6 | Day 6 Part 1 | 24 min | |||||
| Linear combinations of RV’s (3.1.4) | Day 6: slides 7-10 | same | same | Day 6 Part 2 | 14 min | ||||
| Binomial dist (3.2) | Day 6: slides 11-15 | same | same | Day 6 Part 3 | 27 min | ||||
| 7 | Normal dist and prob’s for standard normal (3.3.1, 3.3.3) | Day 7: slides 1-5 | Day 7 Part 1 | 27 min | |||||
| Normal prob’s using z-scores (3.3.2, 3.3.4) | Day 7: slides 6-7 | same | same | Day 7 Part 2 | 15 min | ||||
| Normal approx of binomial dist (3.3.6) | Day 7: slides 8-9 | same | same | Day 7 Part 3 | 14 min | ||||
| Poisson dist (3.4) | Day 7: slides 10-12 | same | same | Day 7 Part 4 | 15 min |
Class discussion
During class you will be working in groups discussing the following:
Day06
- Example 3.11 on pg 6 of slides
- Example 3.17 on pg 10 of slides
- Hint: If you are unsure how to define the random variable T, take a look at how we defined the random variable M in example 3.16 for the amount of money one gets from 3 rolls of a die.
- Example 3.22 parts (1) and (2) on pg 14 of slides
- From HW 3
- Book exercises
- 3.4, 3.8
- Non-book exercise
- NB 1
- Book exercises
- If you want some R practice, try the following:
- Example 3.3 on pg 2 of slides
- Write R code to calculate the expected value by defining vectors in R with the relevant values and then doing the appropriate calculations with the vectors.
- Hint: start with
x <- 1:6.
- Example 3.10 on pg 5 of slides
- Write R code to calculate the variance and standard deviation by defining vectors in R with the relevant values and then doing the appropriate calculations with the vectors.
- Example 3.3 on pg 2 of slides
Day07
- Example 3.3 parts (1) and (3) on pg 7 of slides
- Example 3.8 parts (2) and (3) on pg 11 of slides
- From HW 3
- Book exercises
- 3.22, 3.32, 3.40
- Book exercises
Homework
- HW 3 due on Sat, 10/26
- Make sure to check out the calculating probabilities in R code file: qmd, html
- Note: the answer to exercise 3.31(b) in the textbook (not assigned) is incorrect.
- Check out this spreadsheet for more typos in book.
Exam 1 information
- Exam 1 will be on Wed, Oct. 30th
- Samples of past exam questions and answers (on Sakai)
- Material will cover Days 1-7,
- which is approximately Chapters 1, 2, 3.1-3.4 from the textbook.
- The exam will be in-class and handwritten. Bring a calculator.
- You may bring one page of notes on an 8.5” x 11” sheet of paper.
- You may use both sides.
- You may type your notes.
- You may not use screenshots of the notes or textbook
- You will be turning in the page of notes with the exam, so please add your name to the sheet.