Spring 2021 – Math 58B HW

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 1:30 – 3pm 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 Islands Project:

3/31/21: Pilot Study — research question, methods section, preliminary data

4/14/21: Power Analysis – calculation of sample size from the Pilot data

4/21/21: Preliminary Data Analysis — data summaries / visualizations, first draft of analysis, including regression

5/5/21: Full Draft – including multiple regression

5/7/21: Presentation — 2 slides, < 5 min presentation during lab time.  You can create a video if you prefer to send that instead of presenting.

5/13/21: Final (edited) Project

5/13/21: Project Rubric

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 (as in HW 8)

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!