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Introductory Statistics: Study Design, Analysis and Interpretation for Epidemiology, Public Health and Social Sciences

Course Description

Do you need to use survey or intervention data sets in your research? Or do you need to be able to understand and interpret quantitative papers published in your research area?

Attended some statistics lectures but still find statistics confusing?

Not sure how to apply what you’ve learnt in other introductory statistics courses to your everyday research?

The emphasis of this course is on using group work to help students apply their basic statistics knowledge and training to real problems. Students and researchers undertaking quantitative research projects often need to know how to frame their research questions, define hypotheses, select an appropriate study design and then answer those research questions and test those hypotheses using a variety of statistical tests. Using a series of example scenarios, this course helps students apply basic statistical methods to empirical research and develop their own research designs.

The course covers:

  • Introduction to study design
  • Testing research questions
  • Summarising and presenting data
  • Sampling
  • Power and sample size

The course is run over six two-hour sessions and consists of a series of research problems drawn from epidemiology and public health for which students are asked to find solutions, working in small teams akin to that of an academic or public sector research team. Small group work is facilitated by an experienced data analyst and is supplemented by mini-lectures and discussions. Short one-to-one tutorials for students with a particular issue with their own data are also available.

Students should come prepared to contribute to group and whole class discussions and be able to attend all the sessions. We will focus on the basics of good study design, practicing formulating research questions as testable hypotheses, finding out what size your study needs to be, selecting appropriate statistical tests for the data, and presenting your analysis. The course does not involve any computing though will use computer generated output for analysis purposes.

A more advanced level course is also available entitled Statistical Analysis Methods for Epidemiology and Social Sciences

"Very helpful for revision. Also helpful for introducing other aspects requiring consideration. It was interesting to meet members from various disciplines and hear about other areas of research and difficulties encountered."

"Amazing course, immensely helpful even for final year PhD students. Very clear and supportive course leader."

"Excellent opportunity to consolidate knowledge of study design and basic statistical ideas. But most useful to hear others' research ideas and the dilemmas of putting ideas into practice being mindful of wider design and interpretation restraints."

"An excellent course pitched at just the right level for new PhD students in social/population sciences. A very good balance between theory and practical application of course material illustrated with instuctive examples from students' and tutor's own work. Well worth attending and I would recommend it very highly to other students."

"This course is an ideal refresher for those who have some basic training in statistical research methods. There are plenty of worked examples along with excellent support and tuition to ensure you understand the concepts and methods covered."

Researcher Development Framework Categories

A1) Knowledge base

Course Recommended for

This course is particularly relevant to the following groups:

  • Students in Social & Historical Sciences
  • Students in Life Sciences
  • Students in Medical Sciences
  • Students in Population Health Sciences

Course Organisers

  • Course Tutor - Dr Nicola Shelton - (Research Department of Epidemiology & Public Health)
  • Course Tutor - Dr Paola Zaninotto - (Research Department of Epidemiology & Public Health)
  • Course Tutor - Prof Jenny Head - (Research Department of Epidemiology & Public Health)
  • Administrator - Ms Kasia Bronk - (Organisational Development)

 

5 Nov-10 Dec 2014 expand

Page last updated: 23rd April 2015