This is the reading that should be done for each lecture before you attend the lab session. Please please please do this reading before you come to the lab in order to make the most of the lab time. It will help if you are alread familiar with the concepts when you begin to apply them. They are not long, some of them are videos, and almost all of them are available online with your library login. There is literally no way of making this easier to access and read, short of reading it out loud to you. The links should send you directly to the relevant reading, although you will have to log in with your university username and password.
If you want to read something cover to cover, I would recommend Tiger That Isn`t, written by Michael Blastland & Andrew Dilnot.. Very easy, very light, and will give you a good feeling about stats (I hope). I will also put other recommended reading at the end of this list.
Mandatory reading for before the session
Week 1. Data sets & variables
Week 2. Describing and visualising single variables
Week 3. Making comparisons I: the basics
Week 4. Concepts, operationalisation, measurement, and Sampling
Week 5. Making comparisons II: the relevance of research design
Week 6. Data visualisation
Week 7. Looking at trends
- Dorling, D., & Simpson, S. (n.d.). Statistics in society : the arithmetic of politics . London: Arnold.
- Chapter 13: ‘Models Are Stories Are Not Real Life’ NOTE: THIS IS NOT AVAILABLE ONLINE YOU HAVE TO GO TO LIBRARY TO FIND HARD COPY
- Read this ONS report on the seasonality of crime - download link
- Wilkinson, L. (2005). The Grammar of Graphics (Second Edition.). New York, NY: Springer New York. https://doi.org/10.1007/0-387-28695-0
- This paper on crime seasonality and its variations across space: Andresen, M. A., & Malleson, N. (2013). Crime seasonality and its variations across space. Applied Geography, 43, 25-35.
Week 8. Qualitative data
Read:
- Silver, C. and Lewins, A. (2014) ‘Chapter 1 Qualitative Data Analysis and CAQDAS’ from their book Using Software in Qualitative Research: A Step-By-Step Guide (p.9-34) - link on Blackboard.
- Silver, C. and Lewins, A. (2014) ‘Chapter 5 Early Steps in Software: Practical Tasks and Familiarisation’, again from the same book book (p.106-133) - link on blackboard.
Also watch the following two videos. These are taken from the QSR NVivo website where there are lots of good tutorials on how to use NVivo to analyse and manage your qualitative data. Feel free to explore further too…
If you’re a Mac user you can also watch the equivalent tutorials for Mac here.
Week 9. Qualitative data analysis
Read:
- Silver, C. and Lewins, A. (2014) ‘Chapter 7 Qualitative Coding in Software: Principles and Processes’ from their book Using Software in Qualitative Research: A Step-By-Step Guide (p.9-34) - link on Blacboard
- Seale, C. (2004) ‘24 Quality In Qualitative Research’ in Seale, C., Gobo, G. Gubrium, J. F. and Silverman, D. (eds) Qualitative Research Practice, London: Sage (p.379-390) - link on Blacboard
Also watch the following two videos:
If you’re a Mac user (like me, and Reka!) you can also watch the equivalent tutorials for Mac here.
Week 10. Wrap up and project support
No preparatory reading required