Here is a PDF version of Method Camp's 2017 Syllabus.
Dates of camp: Tuesday September 5th to Friday September 8th
Time structure of camp:
Breakfast: 9:00 AM
Morning session, math: 9:30 - 11:30 AM
Lunch session (qualitative methods): 12:00 - 1:30 PM
Afternoon session, programming : 2:00 - 4:00 PM
Location: 165 Wallace Hall
Office hours: 4:30-6:30 PM every day, 165 Wallace Hall (Note: in the past, students have found it helpful to use office hours as a time to just work on the homework together in one place)
Gill, Jeff. Essential Mathematics for Political and Social Research. Cambridge University Press. 2006. ISBN: 978-0-521--68403-3. Can buy for <$50 on Amazon (please purchase over the summer for the pre-camp review materials. The summer assignment will adhere pretty closely to the structure of the textbook): Gill on Amazon
Bring computer to camp with R and Rstudio installed
Programming is learned best through practice rather than through passive listening, so each day we're going to have a short activity/assignment where you will apply the lessons learned in that morning's programming lecture. The assignment will be due at 9 AM the following day (right before next day's programming lecture) on Blackboard .
For working on the assignment in and out of class, we'll randomly draw pairs at the end of each programming lecture and your pair will turn in one copy as a group. You'll have some time at the end of each programming lecture to work on the activity but may also need to spend some time on it out of class.
Because the focus will be on these worksheets, there are no required DataCamp modules-- instead, we'll list the relevant DataCamp modules as optional references if you want more practice at another time. Likewise, the listed Gill readings can be used as references but aren't required before camp.
We'll be available in office hours and on Piazza to offer help on the assignment.
Math: Calculus and its Applications
Review of summer assignment topics: chain rule, derivatives of logs/exponents
Two tools useful for optimization: higher-order derivatives and partial derivatives
Preview simple case of univariate optimization
Reading: Gill Chapter 6, and Chapter 5 for those who are newer to calculus
Selected online resources (these are all just suggestions, but ones we've found helpful!):
Lunchtime qualitative speaker: Matthew Desmond
Computing: Review of Basics
Summer review, indexing and manipulation of four main data structures: vectors, lists, matrices, and data.frames
Three useful tools for data manipulation: logical statements, control flow, for loops
Dplyr as a tool for data manipulation
Selected online resources:
Relevant DataCamp modules: Intermediate R
Math: Matrix Algebra
Vectors -> matrices
Addition, subtraction, multiplication
Linear independence
Rank, inverse of a matrix
Matrix applications: distance measures, dimension reduction, using matrices to solve systems of linear equations
Reading: Gill Chapters 3-4
Selected online resources:
Lunchtime qualitative speaker: Fred Wherry
Computing: Functions and the Apply family
Math: Basic Probability
Counting, sets, methods of counting and sampling
Conditional Probability and Baye's Rule
Independence
Reading: Gill chapter 7
Selected online resources:
Lunchtime qualitative speaker: Patricia Fernandez-Kelly
Computing: Data Cleaning and more Advanced Manipulation
Math: Basic Optimization; Open-ended Q & A
Numerical optimization: Newton-Raphson
Maxima and minima: critical points, Hessians
Application: Likelihood Functions
(if there is time) Optimization beyond univariate case: multivariable function
(if there is time) Optimization beyond univariate case: quadratic form notation
Open-ended Question and Answer session about material covered this week
Reading: Gill 6.4-6.9
Selected online resources:
Lunchtime qualitative speaker: Bob Wuthnow
Computing: Plotting and Review of Day 1 material; Open-ended Q & A
Here are DataCamp modules that cover topics in using R that we expect you to be familiar with by the start of camp. Some of you are already very familiar with R, and as a result, we’re not requiring that the modules be completed (in contrast, we are requiring completion of the written assignment). Instead, the modules are there for those new to R to learn the basics of the language so that they have a foundation that we’ll spend a lot of time building upon the week of the camp! R and Rmarkdown each have a learning curve, so as mentioned on the assignment, we encourage you to setup a time to talk on skype or to use Piazza once available to get help. If you’re getting stuck on a module, definitely feel free to just view the solution and take notes to learn from it rather than getting frustrated/giving up.
Here is Method Camp's 2016 Syllabus.
You can also check out the syllabi for the Princeton Sociology PhD statistics courses, taken by all sociology students in their first year, SOC 500 and SOC 504.