Data Science for Brain and Behaviour 1
The module will provide an introduction to data science principles and techniques for undergraduate students studying psychology. 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
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.
By the end of the module you should be able to:
- Demonstrate mastery of the selection and use of programming tools and methods for data analysis
- Write clear and well-organized code to load, clean, filter and explore data in different forms
- Apply simulation and resampling methods for statistical inference
- Choose and apply appropriate visualization and analyses to novel data
- Interpret results from analyses appropriately
- 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
Data Science Project
Individual Reflective Statement