|When||Time||Description||Add to your calendar|
|20 November 2017||11:30||Python is increasingly used by social scientists to collect, process and analyse new types of unstructured or semi-structured data, such as online text and social media data. It is a an accessible, yet versatile programming language which is also broadly used for data science and machine learning tasks, combining multiple types of data, simulation and visualization. This workshop provides an introduction to basic programming notions in Python, and introduces some of the most useful packages used in social science research. No previous programming experience is required.
NOTE: This workshop is a prerequisite for the following Q-Step workshops (to be offered this and next term): Collecting Social Media Data, Data Analysis in Python, Text Analysis.. Full details|| Add event|
|30 November 2017||14:30||At the workshop we will consider basic principles of designing field and survey experiments. We will start with discussing the idea of causal inference and randomisation. Then we will review several experimental designs: completely randomised, stratified, paired, cluster randomised, factorial. Next, we will discuss statistical power in experiments and conclude with a review of the methods for the analysis of experimental data, such as ANOVA and linear model. The workshop will be useful for Q-Step undergraduate students planning to use experiments for their dissertations, as well as for postgraduate students. Full details|| Add event|
|7 December 2017||16:30||This workshop provides an introduction to the main methods used to access, download and store social media data. You will learn how to use Twitter's APIs to collect tweets and user details, and how to collect Facebook posts and comments. Basic knowledge of programming in Python is required, and participants are required to attend the "Intro to Python" workshop first.. Full details|| Add event|