This course will introduce the basic research methodologies used when you are interested in frequency data, differences between groups or relationships between variables. We will also examine consider reliability and validity in research and sampling issues.
In this course we will consider the skills needed to think critically about information, research and statistical analysis. This will cover both primary sources of research and media representations of research. How do we know whether a piece of research is really showing us what the author tells us? To what extent do media representations of science and research really reflect the findings?
Whenever conducting any form of research it is vital to ensure that the highest possible ethical standards are maintained. In this course we will discussed the standard ethic guidelines for conducting research, how to design ethical studies and how to deal with potentially unethical problems.
The way in which a questionnaire is designed can greatly influence both the quality and the quantity of the data collected. In this course we will discuss how to write the questions, different way of collecting responses (rating vs. open ended questions), reliability and validity in questionnaires and we will give a basic overview of the types of analysis typically used to analyse the data collected from questionnaires.
When designing an experiment there are a great many factors that need to be considered. In this course we will talk about experimental and quasi-experimental designs, control variables, confounding variables, the advantages and disadvantages of repeated vs. independent measures designs and the interpretation of main effects and interaction terms.
This is a "no numbers" introduction to the theory behind hypothesis testing and the use of inferential statistics. In this course we will consider how we can collect data from a relatively small number of people and then use statistics to understand whether the patterns in the data can be generalised to the wider population: inferential statistics.
This session will begin with an introduction to the main psychological theories of personality and intelligence. The methodology behind psychometric testing will then be discussed before moving on to looking at a range of different psychometric tests. The tests used for demonstration purposes can be altered to suit your needs.
Measures of central tendency and dispersion. Graphing data, when to use different types of graphs and how to design an effective graph.
Chi square (analysis of frequency data), t tests (differences between groups) and correlations (relationships between variables).
t tests and one-way ANOVA (both independent and repeated measures).
Factorial ANOVA and ANCOVA.
Correlation, linear regression and multiple regression.
Complex regression modelling (stepwise and hierarchical), dummy variable modelling and logistic regression.
Factor analysis and reliability analysis.
Giving a presentation can be a daunting experience at the best of times, but when you are presenting research and statistics it can be terrifying! Our new half-day course will help you to prepare and present both oral and poster presentations. This is a fun and interactive session covering the following topics:
- - Why did you do it? Establishing the background to your research.
- - Presenting methods and analysis.
- - Graphing data: The "rules" for how best to graph your data vary according to how and where you are presenting.
- - Making the most of Powerpoint for your presentation.
- - Oral vs. poster presentations: how should they differ?
- - How to prepare for your talk.
- - Dealing with nerves.
- - Dealing with questions from the audience.
Public speaking may not be comfortable for some, but take our word for it, nerves are good. Being 'centre stage' is not a good place to feel too comfortable, until you get very used to it.
Nerves will keep you "on your toes" and ensure you don't get too complacent. Hard to feel complacent when your heart is beating so hard you're sure everyone watching you can hear it.
If channelled well, nerves can make the difference between giving a humdrum presentation and giving one that keeps people listening.
These courses have been designed in such a way that they can function as stand alone modules, or they can be combined to provide a longer course. The research methodology courses and statistical analysis courses can be successfully combined to give a broad and thorough training.
Please contact us to discuss your requirements and we can design a course to specifically meet your needs.
Course design and support
- - Participants will be provided with handouts of the course materials and access to a large number of datasets will be provided on our website.
- - Continuing support via email will be available for three months after the course has taken place (subject to agreement and costs – see below).
- - A half day “open session” can be combined with your training needs to provide continuing support. In this session any questions can be asked,
clarifying and further discussing issues covered in the course or establishing how the methods learned can be applied to your own needs. This session is only
available in combination with taught courses.
Costs
- - We have very competitive rates for half day and full day training sessions as well as continued support costs.
- - Discounts are available for academic institutions and charities.
- - Please contact us for more details. We will discuss with you your training needs, put together a fully customised course and give you a quotation.
Examples of course combinations
One day course on understanding research
- - Thinking critically about research (research methodology)
- - Ethics in research (research methodology)
One day course on the basics of statistical analysis
- - Hypothesis testing and inferential statistics (research methodology)
- - Basic statistics (statistical analysis)
One day course on questionnaire design and analysis
- - Issues in questionnaire design (research methodology)
- - Analysis of questionnaire data (statistical analysis)
Two day course on analysis of relationships between variables
- - Hypothesis testing (research methodology)
- - Basic statistics (statistical analysis)
- - Analysis of relationships 1 (statistical analysis)
- - Analysis of relationships 2 (statistical analysis)
Four day intensive training in research methodology and statistical analysis
- - Introduction to research methods (research methodology)
- - Thinking critically about research (research methodology)
- - Hypothesis testing (research methodology)
- - Basic statistics (statistical analysis)
- - Analysis of differences 1 (statistical analysis)
- - Analysis of differences 2 (statistical analysis)
- - Analysis of relationships 1 (statistical analysis)
- - Analysis of relationships 2 (statistical analysis)