Data Analysis in the Social Sciences
Here will be published the materials of the course "Data Analysis in the Social Sciences", taught at the Master programme "Politics. Economics. Philosophy." in 2018-2019 academic year.
- Instructor: Alla Tambovtseva
- Modules: 2-4
- Course syllabus: link
During this course we will use R as a programming language and RStudio as a GUI.
How to install R and RStudio?
2. Download RStudio (you need RStudio Desktop Open Source License) and install it on your computer. It is recommended to create a shortcut for RStudio during installation.
How to use RStudio?
Read the instruction here.
For successful submission of assignments you should be able to create and save R code files (.R). However, it would be helpful for your own research projects to learn how to create RMarkdown files.
|01 November||Data collection-1. Population and samples.||lecture1||r-intro||RMarkdown: official page, cheatsheet|
|08 November||Data collection-2. Sampling. Sources of bias.||lecture2||r-types r-vectors|
|15 November||Data types. Intro to exploratory analysis.||lecture3||r-dataload Titanic||csv in R files|
|22 November||Exploratory analysis. Data visualisation.||lecture4||Chile codebook r-explore1||sample quartiles|
|29 November||Exploratory analysis.||[lecture5]||r-tables Chile r-rnorm||wordcloud code|
|10 January||Statistical estimates. Statistical laws.||lecture6||r-loops [r-laws]|
R lectures in pdf
We will use two books as compulsory for this course:
- D.Diez et al. OpenIntro Statistics. 2015. (freely&legally available online)
- Ch.Weelan. Naked statistics. 2013.