Instructors: Jess Kunke and Adam Visokay

Note for participants: Please see emails and this page for updates before and during the math camp.

Monday, September 9: Parrington Hall, room 320 (9:00am-2:00pm)
Parrington Hall, room 360 (2:00pm-5:00pm)
Tuesday, September 10: Mechanical Engineering Building, room 238 (9:00am-5:00pm)
Wednesday, September 11: Parrington Hall, room 320 (9:00am-2:00pm)
Parrington Hall, room 360 (2:00pm-5:00pm)
Thursday, September 12: Parrington Hall, room 360 (9:00am-5:00pm)
Friday, September 13: Parrington Hall, room 320 (9:00am-2:00pm)
Parrington Hall, room 360 (2:00pm-5:00pm)

9am-12pm: Review math concepts, do practice problems

12-1pm: Lunch/break

1-2pm: Office hour/extra practice

2-4pm: Introduction to R programming language

Slides and materials will be linked in the schedule below as they are made available. Much of the course material provided here was first created by Laina Mercer with developments by Jessica Godwin, Peter Gao, Jess Kunke and Erin Lipman.

Tentative calendar (will be continually updated during the camp):

Day	Math Concepts (AM)	R Lab (PM)
Day 1	Mon 9/9
	Part A: Notation, logarithms, exponents, functions, and algebra. Lecture A Slides (click here) Lecture A Slide Annotations (click here) Practice Problems 1 (click here) Practice Problem Solutions 1a (click here) Part B: Linear equations, systems of equations, and limits. Lecture B Slides (click here) Lecture B Slide Annotations (click here) Practice Problem Solutions 1b (click here)	Lab 1 notes document (click here) Intro to computing, R and RStudio Basic operations and variables in R Reading in and exploring data
Day 2	Tue 9/10
	Matrix algebra, matrix arithmetic, determinants, linear equations, and least squares. Lecture Slides (click here) Lecture Slide Annotations Parts 1 (here) and 2 (here) Practice Problems 2 (click here) Practice Problem Solutions 2 (click here)	Lab 2 notes document (click here) and data (here) Reading in data from a file Data exploration Data manipulation with tidyverse Script we wrote in class Days 2-3 (click here)
Day 3	Wed 9/11
	Derivatives and optimization (finding minima/maxima) Lecture Slides (click here) Lecture Slide Annotations (click here) Practice Problems 3 (click here) Practice Problem Solutions 3 (click here)	Lab 3 notes document (click here) Data manipulation with tidyverse (continued) Data visualization Matrices in R Day 3 Script (click here)
Day 4	Thu 9/12
	Intro to probability (sets, basic rules, conditional probability) Random variables (bernoulli, binomial, uniform, normal; expectation, variance) Probability distributions (pmfs/pdfs)) Lecture Slides (click here) Lecture Slide Annotations (click here)	Lab 4 notes document (click here) Solving problems using simulations Probability and sampling Benchmarking For-loops Writing your own functions in R Day 4 script (click here)
Day 5.	Fri 9/13
	Integrals, Numerical approximation to integrals, Monte Carlo integration Flex time to go over anything that was confusing/could use more practice Lecture Slides (click here) Lecture Slide Annotations Parts 1 (here) and 2 (here) Practice Problems 5 (click here) Practice Problem Solutions 5 (click here)	Lab 5 notes document (click here) Lab 5 example Quarto doc (click here) Finish Day 3 plots (multiple curves in a plot; facets) Quarto Extra data analysis/plotting practice! Day 5 R script (click here)