STATS 506, Fall 2023
Computational Methods and Tools in Statistics

Course Material

Syllabus

Assignments

Preliminary Assignment - Git/Github
Problem Set 1 due Sep 12
Problem Set 1 Solutions
Problem Set 2 due Sep 26
Problem Set 2 Solutions
Problem Set 3 due Oct 10
Problem Set 3 Solutions
Problem Set 4 due Oct 24
Problem Set 4 Solutions
Problem Set 5 due Nov 21
Problem Set 5 Solutions
Problem Set 6 due Dec 5
Problem Set 6 Solutions

Midterm & Final Project

Midterm details
Midterm
Midterm Solutions

Final project instructions

Lecture Notes

01 - Introduction to R
02 - Quarto and RMarkdown
03 - Version Control and Git
04 - Vectorization and Monte Carlo
05 - Debugging Function in R
06 - Fitting Models in R
07 - Stata
08 - SQL
09 - Regular Expressions
10 - Other Statistical Software
11 - The Tidyverse
12 - R Visualization - Base R and ggplot2
13 - R Visualization - plotly (Version with no plots)
14 - SAS Fundamentals (sas_oda.zip, sas_oda2.zip - only needed if you are not using SAS OnDemand)
15 - R’s OOP
16 - data.table
17 - Parallel Processing
18 - Futures
19 - High Performance Computing
20 - Unix Skills
21 - R Packages, polypack repo

Scripts from Lecture

These are the scripts I work on during class. I make no promises that these are complete or useful.

Aug 29
Sept 7 [1, 2]
Sept 19
Sept 28 [1, 2]
Oct 24
Nov 9 [1, 2]
Nov 21

Aug 31
Sept 12 [1, 2]
Sept 21 [1, 2]
Oct 3
Nov 2
Nov 14 [1, 2]

Sept 5 [1, 2]
Sep 14
Sep 26
Oct 10
Nov 7
Nov 16 [1, 2]

Case Studies

Case Study 1: Stata (9/21/23)
Files: 01-import.do, 02-merge.do, 03-variables.do, 04-bivariate.do, 05-analysis.do

Case Study 2: MS Daily Data (10/24/23)
Files: msdaily-tidyverse.R, msdaily-baseR.R

Case Study 3: InfinitySparseMatrix implementation (11/9/23)
- InfinitySparseMatrix.R
- Matching slides - Some slides with more information on matching and optmatch for more context on InfinitySparseMatrices..

Miscellanous

Developing a Consistent R Style
Response Surface script
mc.cores argument to mclapply