Spring 2021 Math 58B HW Schedule
Introduction to Biostatistics
Math 58B, Spring 2021
Jo Hardin
2351 Estella Laboratory
jo.hardin@pomona.edu
See Sakai for all relevant links
Office Hours (on Discord, see Sakai for link):
Tuesday 8:30-9:30am PT and 3-4pm PT
Thursday 7-8am PT and 12-2pm PT
Friday 9-10:30am PT
or by appointment
Mentors: TBD
Important Websites:
- Main course page
- Schedule / Homework Assignments
- Course Notes
- Main text: Introduction to Modern Statistics
- Applets: ISCAM
- Supplementary text / examples: ISCAM
- infer help
- rstudio.pomona.edu
Exam 1 (date: Friday, March 5)
Exam 2 (date: Friday, April 30)
Final Data Analysis Project (date: end of semester-ish, maybe last week of classes, maybe Thursday May 13)
Text: I will follow Introductory to Modern Statistics reasonably closely (https://openintro-ims.netlify.app/). I have posted the daily sections on the course homework page. It would do you well to read over the text before we cover the material in class.
Many of the examples and all of the applets will be taken from Investigating Statistical Concepts, Applications, and Methods, by Chance & Rossman (if you want to see the details of the examples, you can purchase the R version of the text (.pdf) here for $5: http://www.rossmanchance.com/iscam3/).
ISCAM website with homework & applets
Handouts:
- Class notes are here: http://st47s.com/Math58/Notes/
- Youtube videos on getting started with R and RStudio: Introduction to RStudio
- Some notes I wrote on R / RStudio / tidyverse / ggplot.
- R documentation / help
- Great tutorials through the Coding Club
- swirl package
- Google for R: http://www.rseek.org/
- R tutorial
- An Introduction to R, Venables & Smith
- R Language Definition, R Core Team
- Another tutorial, with exercises & solutions
- Mosaic Reference Guide, need to install the mosaic package
- A Student’s Guide to R; Horton, Pruim, Kaplan (click on “Raw” to download)
- Data Wrangling Cheatsheet: http://www.rstudio.com/resources/cheatsheets/
- Clicker Questions
- Reflection Questions — see the end of each chapter in online notes
- Confidence Intervals and Hypothesis Testing Cheat Sheet
- Advice for Exam 1
- Advice for Exam 2
- When to use what
Homework:
- Homework will be assigned from the text, posted online, and due to Gradescope every Friday at midnight PT.
- One homework grade will be dropped.
- HW is graded on a scale of 5/4/3/2/1. See the first HW assignment for more information. One point will be deducted if superfluous information is printed or if assignment is excessively long.
- All R HW problems should be turned in as pdf documents compiled from an R Markdown file. Remember: knit early and often!
- Labs will be posted online by Friday mornings and due to Gradescope Wednesday at midnight PT.
- In an ideal world, you will work on the lab synchronously with your classmates on Fridays at 11am PT. If you are working asynchronously, let’s try to find a group for you for the labs.
- One lab grade will be dropped.
- Labs are graded on a scale of 5/4/3/2/1. See the first lab assignment for more information. One point will be deducted if superfluous information is printed or if assignment is excessively long.
- All labs should be turned in as pdf documents compiled from an R Markdown file. Remember: knit early and often!
Date | Topic | IMS section
(base text with HW and reference material) |
ISCAM investigation
(mostly in-class examples & applets) |
Lab due:
Wednesday (midnight PT) |
HW due:
Friday (midnight PT) |
Handouts / article link
for class discussion
|
Warm-up
(due by 5pm PT next day, Gradescope) |
Mon 1/25 | helper infants | Inv 1.1 | Warm-up 1: 1/25 | ||||
Wed 1/27 | variables & studies | 1.2, 1.4 | just read through once (don’t need to know all the details) | Warm-up 2: 1/27 | |||
Lab:
Fri 1/29 |
2 | R & the tidyverse
(see next week for the assignment) |
syllabus quiz (not a real “quiz”): syllquiz.Rmd syllquiz.pdf | ||||
Mon 2/1 | two quantitative variables & correlation | 3.1 | Inv 5.7 | Warm-up 3: 2/1 | |||
Wed 2/3 | least square regression | 3.2 | Inv 5.8 | Lab#1 as .pdf | Warm-up 4: 2/3 | ||
Lab:
Fri 2/5 |
plotting & modeling | HW#1 as .pdf | |||||
Mon 2/8 | introduction to hypothesis testing | 5 | (heads up: about Covid-19 deaths and race) | Warm-up 5: 2/8 | |||
Wed 2/10 | randomization test | 5.1 | Lab#2 as .pdf | Warm-up 6: 2/10 | |||
Lab:
Fri 2/12 |
infer | 5.1 | HW#2 as .pdf | ||||
Mon 2/15 | introduction to confidence intervals | 5.2 | Inv 1.10 | New Drugs Stir Debate on Rules of Clinical Trials | Warm-up 7: 2/15 | ||
Wed 2/17 | bootstrapping | Lab#3 as .pdf | Warm-up 8: 2/17 | ||||
Lab:
Fri 2/19 |
infer | HW#3 as .pdf | |||||
Mon 2/22 | CLT | 5.3 | Is Alcohol Good for You?
(pdf version on Sakai) |
Warm-up 9: 2/22 | |||
Wed 2/24 | math approx | Lab #4 as .pdf | Warm-up 10: 2/24 | ||||
Lab:
Fri 2/26 |
The Islands | HW #4 as .pdf | |||||
Mon 3/1 | one proportion / power | 6.1 | Inv 1.7 | Cholesterol-Fighting Drugs Show Wider Benefit
Also this paragraph: Pfizer and BioNTech said they had identified 94 cases of COVID-19 among 43,538 trial participants. The companies did not indicate how many of those cases were in the placebo group or among those who got the vaccine. But they said that the split of cases between the groups suggested that the vaccine was more than 90% effective at preventing disease, when measured at least one week after trial participants had received a second vaccine dose 3 weeks after the first. The trial will continue until a total of 164 COVID-19 cases are detected, so initial estimates of the vaccine’s effectiveness could change. |
Warm-up 11: 3/1 | ||
Wed 3/3 | sampling | 1.3 | Inv 1.12 | Lab #5 as .doc
(not due!) |
HW #5 as .pdf
(due Wed not Fri!) |
||
Lab:
Fri 3/5 |
NO LAB:
Exam 1 (take home) |
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Mon 3/8 | spring break | ||||||
Wed 3/10 | spring break | ||||||
Mon 3/15 | two proportions | 6.2 | |||||
Wed 3/17 | relative risk vs
odds ratios |
no lab due | |||||
Lab: Fri 3/19 | no HW due | ||||||
Mon 3/22 | chi-squared test | 6.3 | |||||
Wed 3/24 | one mean | 7.1 | |||||
Lab:
Fri 3/26 |
NO LAB:
Cesar Chavez Day |
Research project proposal due | |||||
Mon 3/29 | two means | 7.2 | |||||
Wed 3/31 | paired means | 7.3 | |||||
Lab:
Fri 4/2 |
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Mon 4/5 | t-procedures (summary) | 7.4 | |||||
Wed 4/7 | ANOVA | 7.5 | |||||
Lab:
Fri 4/9 |
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Mon 4/12 | Inference regression | 8.1 | |||||
Wed 4/14 | Model conditions | 8.2 | |||||
Lab:
Fri 4/16 |
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Mon 4/19 | Multiple regression | 4.1 | |||||
Wed 4/21 | Inference multiple regression | 8.3 | |||||
Lab:
Fri 4/23 |
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Mon 4/26 | catch-up | ||||||
Wed 4/38 | review | ||||||
Lab:
Fri 4/30 |
NO LAB:
Exam 2 (take-home) |
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Mon 5/3 | catch-up / project | ||||||
Wed 5/5 | catch-up / project | Research Project (?) | |||||
Lab:
Fri 5/7 |
Maybe, maybe not | Research Project (?) | |||||
Thursday
5/13 |
Final? 9am? | Research Project (?) |