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||csv in R files|
|22 November||Exploratory analysis. Data visualisation||lecture4||Chile.csv codebook r-explore||sample quartiles|
|29 November||Exploratory analysis||R only||r-tables Chile.csv r-rnorm||wordcloud code|
|10 January||Statistical estimates. Statistical laws||lecture6||r-loops r-laws|
|17 January||Confidence intervals||lecture7||r-conf-ints Chile.csv||visualization by K.Magnusson|
|24 January||Hypotheses testing||lecture8||t-test|
|31 January||Data manipulation with dplyr. Correlation analysis||lecture9||r-dplyr r-corr marketing.csv||more on dplyr|
|07 February||Contingency tables and chi-squared test||lecture10||Lab1 L1-solutions CPDS.csv||stringi: library for text handling|
|14 February||Visualising association between variables||R only||r-visualisation wgi_fh.csv||more on scatterplots|
|21 February||Visualisation with ggplot2||R only||r-ggplot2 wgi_fh.csv||types of visualisation, funny quiz on graphs
interactive bubble plot for inspiration
|28 February||Exporting output via stargazer||R only||stargazer for non-LaTeX users|
|7 March||Comparing multiple groups: ANOVA||[lecture11]|
|04 April||Simple linear regression. OLS||lecture12||r-reg1 2011.csv|
|18 April||Multiple linear regression||[lecture13]||[r-reg2] flats.csv|
R lectures in pdf
01 November: r-intro, 08 November: r-types, r-vectors, 15 November: r-dataload csv-add, 22 November: r-explore1, 29 November: r-tables, r-rnorm 12 January: r-loops, r-laws, 17 January: r-conf-ints, 24 January: t-test, 31 January: r-dplyr, r-corr, 14 February: r-visualisation
- Homework 1 (deadline: 18 November, 23:59)
- Homework 2 (deadline: 20 December, 23:59)
- Homework 3 (deadline: 04 February, 23:59)
- Homework 4 (deadline: 18 February, 23:59)
- Homework 5 (deadline: 27 April, 23:59), link to submit
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.