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WINTER SCHOOL ON STATISTICS

13th January 2020 - 17th January 2020

13-17 January 2020

 

Ulster University

Day 1 and 2

SPSS Descriptive and Inferential Statistics
13-14 January 2020

The Doctoral College, in partnership with the School of Psychology, deliver a Winter School on
Statistics for PhD Researchers. The Winter School consists of one two-day course on SPSS:
Descriptive and Inferential Statistics and one three-day course on General Linear Model with
applications in ANOVA, Regression Analysis and Factor Analysis.

Workshop
Dr James Houston
Length: 12 hours (2 days)
Stage of PhD: Any

Description
This two-day short course is designed for researchers who have little or no experience using statistical
software such as SPSS or who may need a refresher course on methods of dealing with quantitative
data. The course is ideally suited to participants who have, or whose organisations may have,
quantitative data but are unsure of how to analyse it or are unsure of how to get the most information
out of their data. The rationale underlying this short-course is to promote evidence-based decision
making through exploiting data. Participants will be made aware of how they can answer research
questions using various types of data and various types of analyses.
The short course begins with an introduction to the SPSS interface, detailing the many features
available in this statistical software. We will also show participants how to get data into SPSS from
various sources, including databases such as excel. The short-course will to introduce and develop
knowledge of statistical analysis, with specific reference to hypothesis testing; statistical concepts and
techniques; selecting an appropriate statistical technique; the application of statistical software to data
analysis; and the production and interpretation of statistical and graphical output.
The short course will use lectures to provide a clear understanding of the logic underlying the use of
statistical techniques and procedures. However, a greater amount of time will be devoted to giving
participants experience of hands-on use of SPSS. At the end of each day participants will be given the
opportunity to discuss any data they might have, particularly in terms of selecting and applying an
appropriate form of analysis or questions they might have about conducting research in general. No
prior knowledge of SPSS or statistical analysis is required.
Facilitator
Dr James Houston is a Lecturer in Psychology at Ulster University and teaches research methods and
statistics to Undergraduate students. James has published widely in leading journals in the area of
psychological trauma and mental health, mainly employing advanced statistical techniques to examine
relationships within large-scale epidemiological studies. He is currently an expert reviewer for NIHR
and has been involved with peer review with a number of leading journals in both mathematical and
statistical psychology and mental health.
Further information
No prior knowledge of SPSS or statistical analysis is required.
NB: PHD RESEARCHERS MUST BE ABLE TO ATTEND BOTH DAYS OF THE WORKSHOP.

Day 3, 4 and 5

General Linear Model with applications in ANOVA,
Regression Analysis and Factor Analysis
15-17 January 2020

The Doctoral College, in partnership with the School of Psychology, are delivering a Winter
School on Statistics for PhD Researchers. The Winter School consists of one two-day course
on SPSS: Descriptive and Inferential Statistics and one three-day course on General Linear
Model with applications in ANOVA, Regression Analysis and Factor Analysis.

Workshop
Length: 18 hours (3 days)
Stage of PhD: Any

Description
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.

Facilitators
Dr John Mallett, School of Psychology, Ulster University
Professor Gary Adamson, School of Psychology Ulster University
Professor Jamie Murphy, School of Psychology Ulster University

Further information
No prior knowledge is assumed, but some experience of descriptive statistics and hypothesis testing
would be helpful.
General Linear Model with applications in ANOVA,
Regression Analysis and Factor Analysis

A small number of spaces are reserved for NINE DTP award holders. To register your interest for a place, please email contact.nine@durham.ac.uk before 30th November 2019 with your contact details, a brief overview of your research project, and your case for attendance (small paragraph)

Details

Start:
13th January 2020
End:
17th January 2020
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