About this course
Page last updated 14 December 2018
We offer one-day courses covering different aspects of applied statistics. Courses are non-credit bearing and are designed for quick learning of the material covered.
Fees for external candidates include refreshments and lunch. Fees for internal candidates include refreshments only. Any course materials, including pre-reading, are included in the fee.
We would expect you to have completed the courses 'Introduction to SPSS' and 'Introduction to Inference' or to be familiar with SPSS and have an understanding of statistical inference.
Overseas students need to have, in advance of application, either a valid student visa or evidence of residency status in the UK.
This one-day course will provide hands-on experience of using regression modelling in SPSS. The start of the course will be devoted to modelling a quantitative outcome with respect to a variety of different types of independent variables (factors, covariates, interactions) and different types of model selection procedures as well as considering the statistical validity of regression models. The course will then progress on to modelling binary outcome variables using the very popular approach known as logistic regression. This course is ideally suited to any researcher working with multiple variables which may be related to a dependent variable. SPSS will be used throughout the day with tutor lead examples to explain concepts. This is a practical hands-on course avoiding a mathematical exposition.
This is a non-credit bearing course and no assessment will be undertaken. You will receive a certificate of attendance on completion of the course.
Supplementary fee information
Please see the table below for current fees and discounts available. All prices are VAT exempt.
Discounts can not be used in conjunction with each other. The greatest discount available will be applied at your booking confirmation.
|Cohort||Full Fee||Early Bird Discount||UWE Alumni/Student Discount||UWE Staff Discount|
|Payment Deadline||14 March 2019||25 April 2019||25 April 2019|
(Fees include car parking, lunch and refreshments)
Thursday 9 May 2019
10.00 - 16.00