The module will provide an introduction to data science principles and techniques for students on psychology and neuroscience programmes. Topics covered will include:
1. The role of code in data exploration and analysis
2. Loading, selecting information from and visualizing data sets
3. Programming for data analysis.
4. Data structures, including arrays and data frames.
5. Principles of inference using simulation and resampling.
6. Straight line relationships with correlation and regression.
Students will complete a structured data analysis exercise, in which they explore a novel data set, and do statistical inference to answer questions arising from the data. This will form the basis of the course assessment.
Learning Outcomes
By the end of the module students should be able to:
Select and use appropriate programming tools and methods for analysis of new or existing data.
Write organized code to load, clean, filter and explore data in different forms.
Select and apply appropriate simulation and resampling methods for statistical inference.
Choose and apply data visualizations to different stages of an analysis
Interpret results from analyses correctly and draw appropriate conclusions
Use reflection to identify where code preparation and data analysis strategies were suitable, and where not, and how analysis might be improved in future projects