If your research study employs quantitative or mixed methodologies, you would need to understand the nuts and bolts of statistics and modelling. The Graduate School works with different providers to provide a range of sessions covering descriptive and inferential statistics as well as modelling with esteemed providers such as ISSR and Student Services.

Useful links

Statistical comparisons using R (QCIF) [webinar]

12 August 2024 9:00am13 August 2024 12:30pm
This practical hands-on workshop will help participants to choose and use the appropriate statistical test for their data by introducing key concepts of inferential statistics in R. Prior knowledge of R is required. Please do not sign up unless you are able to fully attend both mornings.

Introduction to Regression modelling (ISSR) [webinar]

19 August 2024 9:00am12:00pm
Learn about simple and multiple regression models.

Exploring and predicting using linear regression in R (QCIF) [webinar]

28 August 2024 9:00am5:00pm
This highly interactive online workshop will provide attendees with a friendly, gentle introduction to the theory behind linear regressions in R. Prior experience with R and the RStudio interface is required, as well as familiarity with the concepts of descriptive statistics and elementary statistical hypothesis testing.

Longitudinal and mixed model analysis using R (QCIF) [webinar]

17 September 2024 9:00am5:00pm
This practical workshop will develop participants’ understanding of the principles, methods, and interpretation of statistical models for longitudinal data. Participants must know R and be familiar with the concepts of statistical hypothesis testing and regression analysis.

Introduction to longitudinal data analysis (ISSR) [webinar]

18 September 2024 9:00am12:00pm
Learn about longitudinal data analysis.

Statistical comparisons using R (QCIF) [webinar]

20 September 2024 9:00am5:00pm
This practical hands-on workshop will help participants to choose and use the appropriate statistical test for their data by introducing key concepts of inferential statistics in R. Prior knowledge of R is required.

Predicting Binary Outcomes using Logistic Regression (QCIF) [webinar]

3 October 2024 9:00am12:30pm
The course will cover the principles of logistic regression and includes practical sessions getting hands-on experience of logistic regression in R. You will require prior expertise in R and a basic familiarity with statistical hypothesis testing and regression analysis to attend.

Statistical comparisons using SPSS (QCIF) [webinar]

11 October 2024 9:00am5:00pm
This practical workshop will help participants to choose and use the appropriate standard statistical test for their data by introducing key concepts of inferential statistics in SPSS. Participants will learn how to compute and interpret hypothesis tests for popular statistical models such as correlation, contingency tables, chi-square test, t-test and ANOVA. Prior knowledge of SPSS is required.

Statistical comparisons using R (CDF) [webinar]

11 November 2024 9:00am12 November 2024 12:30pm
This practical hands-on workshop will help participants to choose and use the appropriate statistical test for their data by introducing key concepts of inferential statistics in R. Prior knowledge of R is required. Please do not sign up unless you are able to fully attend both mornings.

Basic statistical ideas for researchers [webinar]

11 November 2024 10:00am12:00pm
Learn ideas relating to research design, descriptive statistics and inferential statistics.

Longitudinal and mixed model analysis using R (QCIF) [webinar]

23 July 2024 9:00am5:00pm
This practical workshop will develop participants’ understanding of the principles, methods, and interpretation of statistical models for longitudinal data. Participants must know R and be familiar with the concepts of statistical hypothesis testing and regression analysis.

Exploring and predicting using linear regression in SPSS (QCIF) [webinar]

18 July 2024 9:00am5:00pm
This hands-on SPSS workshop introduces principles and methods of regression models using SPSS, and how to interpret relationships between data. It covers basic principles of regression methods through to interpreting the output of statistical analyses. Prior expertise with SPSS is required. Participants are also expected to have a basic familiarity with the concepts of descriptive statistics and elementary statistical hypothesis testing.

Statistical comparisons using SPSS (QCIF) [webinar]

12 July 2024 9:00am5:00pm
This practical workshop will help participants to choose and use the appropriate standard statistical test for their data by introducing key concepts of inferential statistics in SPSS. Participants will learn how to compute and interpret hypothesis tests for popular statistical models such as correlation, contingency tables, chi-square test, t-test and ANOVA. Prior knowledge of SPSS is required.