Advanced SPSS training
SPSS with advanced statistics
This course provides an overview to IBM SPSS for participants with established prior knowledge of statistical processes who plan to analyse quantitative data that they have collected themselves or who plan to analyse existing datasets such as those provided by the UK Data Service.
The material is delivered through a mix of presentation and hands-on experience with the software.
Whilst most of the hands-on experience will take place using example data, participants are encouraged to bring the data they wish to work on for one of the sessions on the second day. Those who do not yet have their data collected will be provided with an example dataset on which to work.
The course covers univariate and bivariate descriptive statistics, as well as inferential bivariate analyses such as t-tests, anova and Chi-square.
Since it can be challenging to successfully collect data that lends itself to these approaches, a significant theme in the course will be the evaluation of how appropriate multivariate regression models are for the analysis of the participants’ data.
In the final presentation session, ‘What could be next?’ participants are introduced to the idea of multi-level analyses and structural equation modelling through examples, illustrating the value-added of such approaches and where they are appropriate.
All our sessions are bespoke.
Although our courses are structured around a logical overview of the quantitative analysis process, we do not deliver mechanical, functional training.
We work closely with you to understand your particular needs and future use of SPSS and design the right content, providing participants with a real sense of how they can best utilise SPSS to meet their particular needs, rather than what the software will allow them to do in a general sense.
The design of each course therefore varies, but examples of what can be included:
Exploring social phenomena using quantitative measures
Types of numerical data: nominal, ordinal, interval and ratio variables
Review of distributions of variables and why these matter for inferential statistics
Guidelines for gathering and working with one’s own quantitative data
Refresher on the SPSS interface and the syntax editor
Understanding variables and how to transform them
Univariate analyses: Generating descriptive statistics of individual variables
Bivariate analyses: Deciding which test is appropriate
Bivariate analyses: Describing and evaluating the relationship between two variables with the appropriate test
Multivariate analyses: Setting up and interpreting a multiple regression model and a multinomial logistic regression model.
Evaluating the potential and limits of one’s own data
Generating output from SPSS for reporting
‘What could be next?’: introduction to the idea of multi-level analysis and structural equation modelling, how they add to your analysis, and where to go to learn more about them.
It is assumed that participants are familiar with the following concepts: levels of measurement, the distribution of variables and their importance for linear regression, standard errors, the sampling distribution, the idea of a null hypothesis and how p-values relate to this, the idea of the linear regression equation, how a linear regression is different from a logistic regression.
Where participants do not feel confident about these concepts and need a refresher, reading material can be suggested.
Participants are encouraged to bring with them a dataset they will be working from during the workshop although sample data can be provided.
This course is tailored to you and can be provided as either a one, two, or three day equivalent session. The exact content will be worked up with you on the basis of participants’ likely uses and need.
Who is this course aimed at?
This training is usually delivered to research teams and institutions and on graduate programmes, although the course is completely tailorable to your organisation.
Format and documentation
All our workshops are hands-on, delivered thorough a blend of demonstration, discussion and practical exercises, rather than providing simplistic, mechanical instruction.
To deliver a tailored experience for participants, we work closely with you to understand their research goals and analytical strategies. Participants will be required to complete a short pre-workshop questionnaire to enable the tutor to focus and tailor the training specifically to attendees’ requirements and cover the most salient topics, as well as specialist needs arising out of individual projects.
Participants are provided with slide decks, reading lists and a range of resources to accompany the course and to support consolidation of the topics covered.
Does this sound right for you? Interested in finding out more? Not quite right, but looking for something similar? Drop us a line to see how we can help.