Reading and Understanding Statistics
This module is for students who don’t plan to use quantitative methods in their own research, but who need to be able to read and understand published research using quantitative methods. You will learn how to interpret graphs, frequency tables and multivariate regression results, and to ask intelligent questions about sampling, methods and statistical inference. The module is aimed at complete beginners, with no prior knowledge of statistics or quantitative methods.
- University Students from Tier 1 Departments
- Further details regarding eligibility criteria are available here
A willingness to learn.
This module is aimed at complete beginners, with no prior knowledge of statistics or quantitative methods
Number of sessions: 4
# | Date | Time | Venue | Trainer | |
---|---|---|---|---|---|
1 | Mon 28 Oct 2019 16:00 - 18:00 | 16:00 - 18:00 | 8 Mill Lane, Lecture Room 1 | map | Dr M.J. Ramsden |
2 | Mon 4 Nov 2019 16:00 - 18:00 | 16:00 - 18:00 | 8 Mill Lane, Lecture Room 1 | map | Dr M.J. Ramsden |
3 | Mon 11 Nov 2019 16:00 - 18:00 | 16:00 - 18:00 | 8 Mill Lane, Lecture Room 1 | map | Dr M.J. Ramsden |
4 | Mon 18 Nov 2019 16:00 - 18:00 | 16:00 - 18:00 | 8 Mill Lane, Lecture Room 1 | map | Dr M.J. Ramsden |
- Background to quantitative research: what is it, how is it different from other kinds of empirical research, and where do data come from?
- Statistical inference and hypothesis testing
- Correlation and tests of bivariate association
- Multivariate analysis
To enable students to understand the fundamentals of academic papers without recourse to formal statistical theory.
Students will learn how to interpret graphs, frequency tables and multivariate regression results, and to ask intelligent questions about sampling, methods and statistical inference.
Presentations, demonstrations and practicals
- Online quizzes may be provided for you to check your own progress
- There is an online open-book test at the end of the module; the test is compulsory for some students – please check with your Department.
The course is not based around a textbook. “Thinking Statistically” by Uri Bram provides a concise and non-technical introduction to the topics covered; Alan Bryman’s “Social Research Methods” goes beyond the material covered in this module, but Part One of the book is well worth reading.
Booking / availability