Welcome to Math Camp!

Offered at the University of Washington each September since 2014, the Center for Statistics and the Social Sciences (CSSS) has provided this math camp as a one-week review of mathematics and probability.

Instructors: Jess Kunke and Erin Lipman, PhD Students in Statistics

Intended audience:

Math camp is open to any entering or current UW graduate students and is particularly suitable for

• Social science graduate students interested in pursuing a quantitatively-oriented research career
• Social science graduate students in the early years of study in departments with CSSS tracks
• Graduate students preparing for advanced CSSS statistics courses

Objectives:

• Prepare students for CSSS and other advanced courses in statistical methodology
• Focus on conceptual foundation, basic tools, and confidence building
• Provide some introduction to programming/statistics in R

This workshop does not assume prior exposure to this material; math skills through high school algebra are helpful but can be reviewed. Part of the purpose of this workshop is that students may use lecture notes and web materials to refresh their memories of key concepts and tools as they continue in research and coursework.

Schedule

Math camp will be offered in a hybrid form this year; participants may participate in person or via Zoom. Our tentative workshop schedule is as follows; please check here for updates. We have reserved both PAR 320 and PAR 360 9-4pm each day.

9am-12pm, The Commons (PAR 320): Review math concepts, do practice problems

12-1pm, The Commons (PAR 320): Lunch/break

1-2pm, The Commons (PAR 320): Office hour/extra practice

2-4pm, Denny Forum (PAR 360): Introduction to R programming language

Slides and materials will be linked to 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 and Peter Gao. Jess and Erin have also contributed to designing the labs.

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Day	Math Concepts	R Lab Content
Mon 9/11	Topic: Algebra and Functions Day 1 Lecture Slides - Part A Day 1 Annotated Lecture Slides - Part A Day 1 Lecture Slides - Part B Day 1 Annotated Lecture Slides - Part B Day 1 Practice Problems	Lab 1 guide Intro to R Studio interface Basic operations and variables in R Reading in and exploring data
Tue 9/12	Topic: Matrix Algebra Day 2 Lecture Slides Day 2 Annotated Lecture Slides Day 2 Practice Problems Helpful Video: Matrix Multiplication	Lab 2 files Lab 2 class script Data manipulation and visualization with tidyverse The concept of tidy data Filter, select, mutate, group_by, summarize Flow from one operation to the next with pipes
Wed 9/13	Topic: Differential Calculus (Derivatives) Day 3 Lecture Slides Day 3 Annotated Lecture Slides Day 3 Practice Problems	Lab 3 files Lab 3 class script and Your Turn solutions Data manipulation and visualization with tidyverse (continued) Making and using a data cleaning script Pivoting to wide and long format Plotting with ggplot2, including facet_wrap and more
Thu 9/14	Topic: Integral Calculus Day 4 Lecture Slides Day 4 Annotated Lecture Slides Day 4 Practice Problems Helpful Video: U-Substitution (definite integrals) Helpful Video: Integration by Parts)	Lab 4 script Lab 4 class script Matrices in R For-loops, vectorization, and code efficiency Benchmarking (timing) your code Writing your own functions
Fri 9/15	Topic: Intro to Probability, Random Variables, Probability Distributions Day 5 Lecture Slides Day 5 Annotated Lecture Slides	Lab 5 files Lab 5 class script Sampling from distributions A quick intro to R Markdown