The course begins by exploring the general linear model and its application in Anova, Ancova, Manova and Mancova with repeated measures models.
This three day short course provides participants with a firm working knowledge of a wide range of statistical models – many of which are the most commonly used statistical models in the behavioural and social sciences.
A 15% discount will be given where the booking is for more than one short course.
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About this course
In this section
Synopsis of the course
This three day short course provides participants with a firm working knowledge of a wide range of statistical models – many of which are the most commonly used statistical models in the behavioural and social sciences. These models also serve as the fundamental building blocks for advanced statistical models and will be particularly useful for those participants wishing to take more advanced short-courses e.g. the Latent Variable Modelling course.
The course begins by exploring the general linear model and its application in Anova, Ancova, Manova and Mancova with repeated measures models. The short-course will describe simple bivariate regression and correlation and build gradually to the multivariate case, which incorporates a number of predictor variables. In addition to examining regression models with a continuous outcome variable, time will be devoted to data situations in which the outcome variable is either dichotomous or polytomous, i.e. binary and multinomial logistic regression models. Moreover, exploratory factor analysis (EFA) will be covered in some depth, with the focus on its usefulness as a data reduction method: the EFA model primarily involve reducing a large number of observed variables to a lesser number of latent factors, the purpose of which is to explain the structural relationship between the observed variables parsimoniously. The short-course will conclude with an introduction to the Confirmatory Factor Analysis models and its applications using advanced statistical software. The assumptions underpinning the use of all techniques will be considered throughout the short-course, together with identifying some strategies for assessing potential violations.
Each element of the short-course will begin with a lecture to provide participants with a sound conceptual understanding of each statistical model and its application. However, greater emphasis will be placed on practical activity, with participants gaining experience using a hands-on approach to reinforce the learning concepts and to ensure that participants are able to perform the desired analysis and appropriately interpret the output. Days 1 and 2 will be taught primarily using SPSS software with Day 3 using both SPSS and Mplus.
No prior knowledge is assumed, but some experience of descriptive statistics and hypothesis testing would be helpful.
Location: Coleraine Campus, Ulster University
If you have any queries about this course, please contact the course tutor Dr Orla McBride at email@example.com
Cancellations made prior to Monday 7th August 2017: full refund less an administrative charge of £50.00.
Cancellations made between Monday 7th August and Monday 14th August: refund of fifty percent.
Cancellations made after Monday 14th August: no refund to be made.
Students can find information relating to accommodation at https://www.ulster.ac.uk/accommodation/forms-and-documents/summer-non-students.
Alternatively please contact James Houston at firstname.lastname@example.org.
This three day course will be held in Coleraine Campus, Cromore Road, Coleraine, BT52 1SA. (Room location tbc).
Date: 22nd-24th August 2018
Time: 9.30 am - 4.30 pm
This three day short course provides participants with a firm working knowledge of a wide range of statistical models.
Price and payment
In this section
You must register and pay for this course online. Fees (including lunch and refreshments).
- Full Fee £450.00
- Concessionary (Unwaged/Students/Charitable sector workers) £300.00
- Full Fee booking with more than one course £382.50
- Discounted Concessionary when booking more than one course £255.00
For further information:
Telephone: (+44) 028 9036 6680