Outline

Jump to bottom Edit New page

François edited this page May 14, 2013 · 4 revisions

Definitely not up-to-date list of sections and contents of the code deployed in the course. Short listing of examples first, longer contents follows.

[011] R: calc, objects [012] RStudio: packages, graphs [013] Hello World!

1_hello.R

[020] addition, logic [021] vectors, matrixes (grades) [022] factors and variables (real grades, BMI) [023] BMI

2_bmi.R

[030] functions [031] conditionals; probability distributions [032] iteration [033] HHI calculations

3_hhi.R

[040] WDI (API) [041] Daily Kos (Google Docs), QOG (CSV, PDF), scraping [042] CSI (reshape) and BJS data (ZIP, selective CSV, reshape) [043] Aggregation with Shor's data (XLSX) and DW-NOMINATE (Stata, aggregate)

4_congress.R

[080] Olympics (forecasting) [081] OECD Better Life (correlation) [082]
Bartels
Hibbs (OLS; partial derivatives, predictions, residuals)
AJR log-settler mortality (partial corr, logged coefs, dummies) http://www-personal.umich.edu/~albouy/ http://www-personal.umich.edu/~albouy/AJRreinvestigation/AJRrev.pdf http://jeffsachs.org/2012/12/reply-to-acemoglu-and-robinsons-response-to-my-book-review/ [083] IMF WEO (outliers)

8_imf.R

[090] ICM Polls (dates, plots) [091] R & R [092] Quandl [093] Piketty & Saez (XLS, aggregate)
[100] Maps [101] Airports (geocoded) [102] [103] Simon Jackman, US two-party vote-shares

Part 1. Basics

0. Essentials

syllabus.pdf
01_intro.R
02_readings.R

Introduction

How we got there
What is data analysis?
Who is this for
Course outline
Course requirements
Disclosure

Readings

Course handbooks
Additional readings
Tutorials
Blogs

1. Setup

Setup

Computer equipment
Computer skills

Installing R

Installation
Commands
Syntax
Assignment
Exit

Installing RStudio

Installation
Interface
Running scripts
Setting the working directory
Tab auto-completion
Packages
Drawing and saving plots
Help pages

Practice session

Folder architecture
"Hello, R World" (redux)

Exercise 1

RStudio interface basics
Command line tricks
Data objects
R functions
R mathematics
Vectors
Help pages
Workspace commands
Disk files
Quitting R

2. Objects

20_basics.R
21_syntax.R
22_vectors.R
23_objects.R

Objects
Vectors and matrixes
Variables and factors
Practice

Exercise 2

a
b
c

3. Functions

30_math.R
31_functions.R
32_loops.R
33_proba.R

Functions
i
i
i

Exercise 3

a
b
c

4. Data

40_data.R
41_dataio.R
42_reshaping.R
43_scraping.R

Data
i
i
i

Exercise 4

a
b
c

Part 2. Analysis

50_clusters.R
51_heatmaps.R
52_pca.R
53_kmeans.R
60_distributions.R
61_descr.R
62_pdf.R
63_ecdf.R
70_hyptests.R
71_ci.R
72_ttest.R
73_prtest.R
80_lin.R
81_scatterplots.R
82_regression.R
83_vwreg.R
- 83_vwreg_ggplot2.R by David Sparks
- 83_vwreg.R by Felix Schönbrodt

Part 3. Extensions

90_ts.R
91_lags.R
- 91_beijing_pollution.R adapted from Roger D. Peng and David Ruau
92_smoothing.R
- example: smoothing trends in assault deaths in the United States
- dataset: Bureau of Justice Statistics (htus8008)
100_maps.R
101_choropleth.R
102_gmaps.R
110_networks.R
- 110_plotg.R adapted from Moritz Marbach
111_influence.R
112_twitter.R
120_data.R