This face to face course is run by the Researcher Academy 

Target audience: This course is for Postgraduate Research Students & Research Staff in the Faculty of Medicine and Health Sciences only  

Pre-requisites:
To attend this course you must have prior knowledge of both basic statistics including the ideas of sampling variability, measures of effect (e.g. odds ratio and mean difference) and tests of statistical significance (e.g. chi-squared test and t-test) and familiarity with SPSS.

This course covers advanced level statistical methods and advanced level usage of statistical software. There will be no opportunity to cover the basics of statistics or SPSS during the workshop. If you are not familiar with SPSS you must attend the Introduction to Statistics with SPSS (classroom) or Introduction to SPSS (online) course in advance of booking/attending.

It is essential that participants have prior knowledge and level of competency in advance of the course (completion of undergrad/masters-level module and/or work-based experience). If not you must cancel your place so it can be allocated to someone else.

Aims:

• To provide understanding of the purpose of multivariate regression models
• To provide knowledge of two important regression models; linear and logistic regression
• To provide practical skills in building and interpreting linear and logistic regression models in SPSS

Learning outcomes:

• Appreciate the different situations in which we might need to use multivariable regression analyses
• Know when it is appropriate to use two of the common multivariable regression models, linear and logistic regression.
• An understanding of how to build, and interpret the output from a multiple linear regression model in SPSS
• An understanding of how to build, and interpret the output from, a multiple logistic regression model in SPSS
• An understanding of approaches to building a model to adjust for confounders
• An understanding of approaches to building a model to best predict an outcome

Process: Classroom lectures and practical exercises in SPSS. The two separate training days associated with this course comprise of: Day 1) Linear Regression in SPSS and Day 2) Logistic Regression in SPSS. 
 

Course Accessibility

The following table shows a summary of what is needed to participate in the course. 

If you feel you will experience any difficulties participating, please let us know via the ‘special requirements’ tab, providing as much information as possible. The special requirements tab can be completed when you book your place. Alternatively, you can contact us directly at bb-ra-training@nottingham.ac.uk

Access and/or complete self-study/ pre-course tasks prior to main session
Print off pre-requisite paperwork/ resources & bring them to the course (optional)
Bring your own laptop/ PC to the course (optional)
Access seminar room on campus
Attend the course at the specified date and time
Watch and listen to the course tutor(s) and/or other attendees
Follow presentation slides during the course

Booking Conditions

Latecomer policy

Researchers should plan to arrive prior to the advertised course start time. Except for exceptional reasons, there will be no admittance to a Researcher Academy or Faculty Training Programme (FTP) course 15 minutes after the advertised course start time.

Importance of booking commitment

When booking on to a Researcher Academy short course you are entering into a commitment to attend. If you find that you are no longer available to attend you MUST cancel your place (on the system if more than three days before the course) or if at short notice by emailing bb-ra-training@nottingham.ac.uk This will ensure that your place can be offered to another researcher on the waiting list. Failure to cancel a place results in other researchers missing out on places through the waiting list process.

It is unacceptable for researchers to just not attend when booked onto a course. The Researcher Academy maintains records of those who repeatedly do not attend courses they have booked. This may affect future eligibility to book onto further Researcher Academy courses and will affect considerations for Researcher Academy funded opportunities.

Pre-Requisites

Pre-requisites

This course is aimed at students and researchers who have a good grasp of basic statistics including the ideas of sampling variability, measures of effect (e.g. odds ratio and mean difference) and tests of statistical significance (e.g. chi-squared test and t-test) and familiarity with SPSS.

This course covers advanced level statistical methods and advanced level usage of statistical software. There will be no opportunity to cover the basics of statistics or SPSS during the workshop.