APSTA-GE 2006: Statistics, Math, and Computing Bootcamp

This is the home for Math, Statistics and R Programming bootcamp offered by NYU PRIISM, the Center for Practice and Research at the Intersection of Information, Society, and Methodology. Registered students will be given access to Brightspace, where we will host an online forum.

The bootcamp aims to prepare students for the Applied Statistics for Social Science Research program at NYU. We will cover basic programming using the R language, including data manipulation and graphical displays; some key ideas from Calculus, including differentiation and integration; basic matrix algebra, including vector and matrix arithmetic; some core concepts in Probability, including random variables, discrete and continuous distributions, and expectations; and a few simple regression examples.

This is the current version of the syllabus, which is subject to change, so please check the date to make sure you have the most recent version.

Topic 01: The Big Picture and Introduction to R
Topic 02: Plotting, Exponentials, Logs, and Derivatives
Topic 03: Reshaping Data, Loops, and Maps; Introduction to Integration
Topic 04: Sample Spaces, Conditional Probability, Independence, Bayes Rule
Topic 05: Random Variables and Expectations
Topic 06: Introduction to Linear Algebra
Topic 07: Statistical Inference
Topic 08: Analysis Workflow and Regression

Course materials and references

Programming and Data Visualization

Hands-On Programming with R, Grolemund, 2014
R for Data Science, Wickham et al., 2023
Data Visualization, A practical introduction, Healy, 2018

Calculus

YouTube: Essence of Calculus, Sanderson, 2018
Calculus Made Easy, Thompson, 1980
Calculus, Herman et al., 2016

Course materials and references

Programming and Data Visualization

Calculus

Probability

Statistics

Linear Algebra