Statistical Methods for Business, Medicine and Social Science
Learn how to apply statistics in a weekend, as we explore the basic statistical methods used in various fields such as business studies, economics, politics, psychology and medicine.
9.00am Introducton and descriptive statistics
11.00am More on descriptive statistics, frequencies
12.30pm Break / Lunch
1.30pm Normal and other distributions, standard score
3.30pm Hypothesis testing - introduction, including significance and type 1 and 2 errors
5.00pm Day One ends
9.00am Specific hypothesis tests - the day includes t test, chi test
11.00am Specific hypothesis tests continued
12.30pm Break / Lunch
1.30pm Specific hypothesis tests continued
3.30pm Correlation and regression
5.00pm Course disperses
Hinton, P.R. Statistics Explained: A guide for Social Science Students (Routledge, 2011 or alternatively the 2004 edition).
Groebner, D.F. and Shannon, P.W. Business Statistics: A Decision Making Appraoch (various editions available)
Wonnacott, T.H. and Wonnacott, R.J. Introductory Statistics for Business and Economics (Wiley, 1990)
Attwood, G., Dyer, G. and Skipworth, G. Statistics 1, 2, 3 (Heinemann, Edexcel 2000)
Accommodation is not included in the price, but depending on availability, it may be possible to stay at Rewley House on Friday and / or Saturday night. Please contact our Residential Centre on +44 (0) 1865 270362 or email firstname.lastname@example.org for details of availability and discounted prices.
Accommodation in Rewley House - all bedrooms are modern, comfortably furnished and each room has tea and coffee making facilities, Freeview television, and Free WiFi and private bath or shower rooms.
Tuition (includes coffee/tea): £182.00
Baguette lunch (both days): £10.00
If you are in receipt of a state benefit you may be eligible for a reduction of 50% of tuition fees.
If you do not qualify for the concessionary fee but are experiencing financial hardship, you may still be eligible for financial assistance.
Director of Studies
Dr Cezar Ionescu is Associate Professor of Data Science with the Oxford University Department for Continuing Education. His main interests include functional programming, correctness of scientific computing and machine learning algorithms, and the role of computing science in education.
Dr Vasos Pavlika is Principal Teaching Fellow at University College London and Saturday School lecturer at the LSE. He has been a lecturer in the Department for Continuing Education, Oxford for several years. Vasos also teaches at the Institute of Continuing Education, Cambridge.
Please use the 'Book' or 'Apply' button on this page. Alternatively, please contact us to obtain an application form.
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