Quantitative Data Analysis
Full course description
In this course you will be introduced to the methods and instruments used by researchers and professionals when designing and analyzing quantitative data in the Humanities and Social Sciences. You will gain skills and knowledge in a range of data analysis methods and visualization techniques to enable you to study cross-sectional, longitudinal and stacked data structures, analyze them employing univariate, bivariate and multivariate techniques, and use these skills to describe data and to draw inferences about society and the ways digital technologies are used, created, and influence our daily lives. This course will prepare you to carry out independent quantitative research. You will have plenty of hands-on experience working individually and within small working groups to conduct small scale, quantitative research projects, analyze the data collected, and present your findings.
At the end of this course, you will be able to:
- Understand the main concepts and building blocks in quantitative research methodology and probability theory;
- Interpret quantitative data analysis results and understand the limitations of statistical testing and how particular tests are used on certain types of data;
- Choose, conduct and implement adequate univariate, bivariate and multivariate statistical analyses using R to test theoretically informed research questions;
- Effectively communicate data analysis and interpretation using statistical tests, tables, graphics and other visuals.
Note that it is very important that you complete this course successfully before you start DSO2003 Working with Big Data.
Agresti, A. (2018). Statistical Methods for the Social Sciences (Fifth edition). Harlow: Pearson.