Data Analysis in the Social Sciences

Материалы по математике, 2018-19 учебный год
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Course info

Dear students,

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

Software

During this course we will use R as a programming language and RStudio as a GUI.

How to install R and RStudio?

1. Download R (you can choose another mirror here if you wish) and install it on your computer. Make sure you did it before installing 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.

Materials

Date Topic Theory R Optional
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-explore1 sample quartiles
29 November Exploratory analysis. 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

socling.csv

stringi: library for text handling
14 February Visualising association between variables. - r-visualisation wgi_fh.csv

Lab2 [L2-solutions]

more on scatterplots

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

Home assignments

Readings

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.