Short course prerequisites
IT requirements for online short courses
Some courses require access to specific statistical software, such as Stata or R.
Please check the requirements for your chosen course before registering.
External participants are responsible for providing their own access to Stata, however if you are a student, Stata do offer a short term student licence for those needing to use Stata for a maximum of one week during a course.
To ensure our courses are suitable for you, and that you can fully benefit from online participation, we identify a number of course prerequisites. We kindly request that you check you have access to the relevant IT resources needed for the course and meet the knowledge prerequisites prior to booking.
Please select a course from the list below to view prerequisites and IT requirements. If your course is not listed there are no specific prerequisites.
Advanced Epigenetic Epidemiology
Please ensure you meet the following prerequisites before booking:
Knowledge |
You should be very familiar with the topics presented in our Epigenetic Epidemiology short course. This includes, in particular, practical knowledge of using R to analyse microarray data. |
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Advanced Mendelian Randomization
Please ensure you meet the following prerequisites before booking:
Knowledge |
The course is an advanced level course in Mendelian randomization and assumes that participants already have knowledge of the basics of MR. Participants should have completed the Mendelian Randomization short-course (or equivalent) and should have experience of conducting MR analyses. Practical sessions will be conducted using R and so participants should have an understanding of using R for data analysis, however previous experience of conducting MR estimation using R is not required. |
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Software |
Practical sessions will be conducted in R and so participants should have a recent version R installed prior to the start of the course. Go to R Installation Instructions for help getting set up. |
Please note this course is a pilot, open to internal University of Bristol staff and students only.
Advanced Multiple Imputation Methods to deal with Missing Data
Please ensure you meet the following prerequisites before booking:
Knowledge |
Prior attendance of the Multiple Imputation for Missing Data short course (or equivalent introductory course to missing data concepts and multiple imputation) or be familiar with the concept of multiple imputation, and have used it in practice. Also, familiarity with standard regression methods for continuous and binary outcomes beyond a basic level. |
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Software |
You must have Stata (version 13 or later)* and R** (version 4.0.3 or later) installed in advance of the course. *Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course. External participants are responsible for providing their own access to Stata. **Go to R Installation Instructions for help getting set up. |
Advanced Survival Analysis
Please ensure you meet the following prerequisites before booking:
Knowledge |
Participants should be familiar with using Stata statistical software and implementing survival analyses within Stata. Participants should also be familiar with the basics of survival analysis, to at least the level attained from the short course on Introduction to Rates and Survival Analysis. |
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Software |
You must have Stata (version 11 or later, though we recommend more recent versions)* installed in advance of the course. *Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course. External participants are responsible for providing their own access to Stata. |
Analysis of Repeated Measures
Please ensure you meet the following prerequisites before booking:
Knowledge | You must be familiar with the algebra of standard regression models for continuous outcomes (to beyond the standard of the short course Introduction to Linear and Logistic Regression Models or to the level implied by module 3 of the Centre for Multilevel Modelling online multilevel modelling course). |
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Software | You must be familiar with either R or Stata. Those using Stata* must have this installed in advance of the course. *Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course. |
Causal Inference in Epidemiology: Concepts and Methods
Please ensure you meet the following prerequisites before booking:
Knowledge |
Applicants must have knowledge and experience of a variety of linear and logistic regression models and their implementation in Stata, to beyond the level achieved in the Introduction to Linear and Logistic Regression Models course. Familiarity with survival analysis is recommended. |
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Software |
You must have Stata* (version 14, 15 or 16) installed in advance of the course. *Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course. External participants are responsible for providing their own access to Stata. |
Economic Evaluation Modelling Using R
Please ensure you meet the following prerequisites before booking:
Knowledge |
You must have at least basic experience using R for statistical analysis. Experience with R is essential (to the level of the Introduction to R short course) but we will review the necessary aspects of R on the first day. You must have experience with decision trees and Markov models (value of information desirable but not necessary). Knowledge of cost-effectiveness analysis, specifically on decision trees and Markov models, will be assumed (to the level of the Introduction to Economic Evaluation short course). |
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Software |
You must have R (version 4.0.0 or higher) and RStudio (version 1.2.5 or higher) installed in advance of the course. Go to R Installation Instructions for help getting set up. |
Epigenetic Epidemiology
Please ensure you meet the following prerequisites before booking:
Knowledge |
A basic knowledge of epidemiology is required and some understanding of molecular genetics terminology would be advantageous. Some practical knowledge of R would be helpful. |
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Recommendation |
Please note that this course attracts a highly multi-disciplinary audience. We do our utmost to accommodate this and ask that if in any doubt, prospective participants enquire prior to booking to check that the course is targeted at the right level for their needs. |
Essentials of Infectious Disease Modelling and Economic Evaluation
Please ensure you meet the following prerequisites before booking:
Software |
Access to a laptop or desktop computer for the duration of the course (joining by mobile/ tablet would be insufficient). Ability to download and install R software (for statistical computing and graphics) to the laptop/desktop prior to starting the course. |
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Genetic Epidemiology
Please ensure you meet the following prerequisites before booking:
Knowledge | Prior experience of genetic epidemiology is not required, but we encourage participants to familiarise themselves with some of the genetic terminology and concepts before the course. To help you to do this we have produced a series of 3 short videos (specifically for this course) which provide a background to basic genetics for those of you who are new to the subject. We recommend you watch these before coming on the course. In addition the following resources both contain some good basic information: https://en.wikipedia.org/wiki/Genetics http://www.dorak.info/genetics/ This course will require students to use analytical software in a command-line Linux and R environment. We will include all instructions but do recommend that you have some experience of these computer environments before the course. |
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Software | During the course, you will run all computer practicals on your own computer/laptop (ideally two screens) using Posit Cloud (formerly known as RStudio Cloud) which allows you access to the R and Linux environments. We will briefly introduce the Cloud in the first practical and provide all main code for all practicals. You do not need to install any software packages yourself. The operating system can be either Windows or Mac and participants should consider having a fast internet speed for synchronous/live sessions and for practicals. |
Improving your Stata: data management, publication-quality outputs, and automating tasks
Please ensure you meet the following prerequisites before booking:
Knowledge |
It is assumed that participants will have attended the Introduction to Stata course (or be familiar with the contents of this course), AND are able to: open and save datasets; generate and rename variables; label variables and values; restrict commands to a subset of the data using the if, in and by qualifiers; generate a Stata date from a string; change the working directory; and use commands display, list, summarize and tabulate. Participants should have a working knowledge of basic statistics such as linear regression. However, the course is focused on data management and programming skills rather than statistical content. |
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Software |
You must have Stata (version 15 or later)* installed in advance of the course. *Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course. External participants are responsible for providing their own access to Stata. |
Recommendation |
A copy of the course manual will be emailed to you in advance of the course. To facilitate practical sessions we recommend that you either print the course manual yourself, have it open on another device (like a tablet or phone), or split your screen between the manual, your own version of STATA and the STATA the tutor is sharing in Blackboard. If available, a second screen would be ideal for splitting your screen between these different programs. |
Introduction to Data Visualisation and Web Applications Using R
Please ensure you meet the following prerequisites before booking:
Knowledge |
Course participants should either have attended the Introduction to R course or be familiar with R and/or RStudio. This course is not intended for people who have never used R before. |
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Software |
This course will use RStudio cloud. Participants will not need to install the desktop version of RStudio to complete the course. If course participants would like to use RStudio Desktop (Open Source version) alongside the cloud version, this is compatible with Windows, Mac and Linux and is freely available from: https://rstudio.com/products/rstudio/download/ (Go to R Installation Instructions for help getting set up.) You will also need software able to open and view .pdf (e.g. Adobe Reader) and .docx files (e.g. MS Word). |
Recommendation |
Participants may find it helpful to have 2 screens. However, this is not a requirement. |
Introduction to Economic Evaluation
Please ensure you meet the following prerequisites before booking:
Knowledge |
No previous experience or knowledge of economics is required. As Microsoft Excel will be used for practical sessions, some experience of using Excel would be helpful. |
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Software |
Course attendees will need access to a recent version of Excel to complete some of the practical sessions. |
Introduction to Epidemiology
Please ensure you meet the following prerequisites before booking:
Knowledge |
This course is intended for clinicians, researchers, public health specialists and other health care professionals who have only a basic understanding of epidemiology. Prior knowledge of basic medical statistics so that you understand findings published in peer-reviewed medical journals is important. |
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Introduction to Linear and Logistic Regression Models
Please ensure you meet the following prerequisites before booking:
Knowledge |
You should have knowledge of statistical methods and their implementation in Stata of at least the level achieved in the Introduction to Statistics short course. |
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Software |
You must have Stata (version 15 or higher)* installed in advance of the course. *Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course. External participants are responsible for providing their own access to Stata. |
Introduction to Network Meta-Analysis
Please ensure you meet the following prerequisites before booking:
Knowledge |
Experience of pairwise meta-analysis (to the level covered by the course 'Introduction to Systematic Reviews and Meta-analysis'), understanding of statistical methods including logistic regression (to the level of the course 'Introduction to Linear and Logistic Regression Models'), and basic experience with R. |
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Software |
You must have R (version 4.0.3 or higher) and RStudio (version 1.3.1093 or higher) installed in advance of the course. This course will use RStudio Desktop (Open Source version). This is compatible with Windows, Mac and Linux and is freely available from: https://rstudio.com/products/rstudio/download/ Go to R Installation Instructions for help getting set up. |
Introduction to R
Please ensure you meet the following prerequisites before booking:
Software |
You must have RStudio installed on your computer in advance of the course. Go to R Installation Instructions for help getting set up. |
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Introduction to Rates and Survival Analysis
Please ensure you meet the following prerequisites before booking:
Knowledge |
Participants should be familiar with the basic Stata commands used to open a dataset, get help on a command, and explore, create and edit variables. Participants should have a knowledge of regression analyses and their implementation in Stata of at least the level achieved in the Introduction to Linear and Logistic Regression Models short course. |
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Software | Participants will need a computer and internet connection capable of video conferencing whilst running Stata (datasets used in the course are all small). You must have Stata (version 12 or later)* installed in advance of the course. *Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course. External participants are responsible for providing their own access to Stata. |
Recommendation |
The Stata practicals will be much easier if you have two screens (one for Stata, one for the instructions). If you do not have a second screen but have access to a printer, we suggest that you print the practical instructions in advance of the course. We will provide these as a printable pdf file. |
Introduction to Research Governance
Please ensure you meet the following prerequisites before booking:
Recommendation | This is an introductory course to research governance. It is not intended to cater for people with advanced knowledge of research governance or complex research governance questions. |
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Introduction to Stata
Please ensure you meet the following prerequisites before booking:
Software | You must have Stata (version 14 or later)* installed in advance of the course. Please note that older versions may be OK, but you should recognise that older versions may have slightly different functionalities. *Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course. External participants are responsible for providing their own access to Stata. |
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Recommendation | A copy of the course manual will be emailed to you in advance of the course. To facilitate practical sessions we recommend that you either print the course manual yourself, have it open on another device (like a tablet or phone), or split your screen between the manual, your own version of STATA and the STATA the tutor is sharing in Blackboard. If available, a second screen would be ideal for splitting your screen between these different programs. |
Introduction to Statistics
Please ensure you meet the following prerequisites before booking:
Software |
Please will students ensure they have access to statistics software before the start of the course. Full support will be given for the use of Stata* in the practical sessions. Students are welcome to use a different package (e.g. R, SAS, SPSS) if they are confident in its use, but we cannot guarantee we will be able to help if difficulties are encountered. *Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course. |
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Introduction to Systematic Reviews and Meta-analysis (A&B)
Please ensure you meet the following prerequisites before booking:
Knowledge |
Participants should have knowledge of statistical methods to the level of our Introduction to Statistics course. A basic appreciation of research designs (to the level of our Introduction to Epidemiology course) would be helpful. Practical session will include implementation of meta-analysis methods in computer software, and either basic knowledge of Stata or familiarity with R would be helpful for this. Students without experience in either will undertake practicals using Stata, and they must have this installed before the start of the course. |
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Software |
Participants must either (i) have access to a computer on which Stata* is pre-installed (version 15 or later) OR (ii) be a regular R user. *Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course. External participants are responsible for providing their own access to Stata. |
Mendelian Randomization
Please ensure you meet the following prerequisites before booking:
Knowledge |
Prior experience of using Mendelian randomization is not required, but participants should have an understanding of aetiological epidemiological principles, and ideally be working on causal population health questions. Those intending to take this course should already understand epidemiological principles and have knowledge and skills in statistical analysis to the level of running, and correctly interpreting results from, multivariable regression analyses. They must have experience in running such analyses efficiently in Stata and/or R as all practicals on the course will be offered in both Stata and R and the focus of these practicals will be on Mendelian randomization (not learning how to use the statistical packages). Note: it is not necessary for those participating in the course to be able to use both Stata and R, but you must be able to use one of these. |
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Software |
Participants who would like to use Stata need to have installed Stata version 16* (or later) in advance of the course. *Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course. External participants are responsible for providing their own access to Stata. **Go to R Installation Instructions for help getting set up. |
Meta-ethnography: An interpretative approach to qualitative evidence synthesis
Please ensure you meet the following prerequisites before booking:
Knowledge |
Previous experience of conducting (or training in) qualitative analysis using an interpretive method such as grounded theory, thematic analysis, narrative analysis, or framework analysis. |
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Multiple Imputation for Missing Data
Please ensure you meet the following prerequisites before booking:
Knowledge |
Familiarity with either Stata or R. Familiarity with standard regression methods for continuous and binary outcomes beyond a basic level, and familiarity with causal diagrams. |
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Software |
You must have either Stata (version 13 or later)* or R installed in advance of the course. You will be offered the choice to do everything in either Stata or R. R can be downloaded for free here. Go to R Installation Instructions for help getting set up. *Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course. External participants are responsible for providing their own access to Stata. |
Optimising Recruitment to Randomised Controlled Trials
Please ensure you meet the following prerequisites before booking:
Knowledge |
It would be advantageous if course attendees have some knowledge and understanding of randomised controlled trials (RCTs). The course does not go into detail about the design/conduct of RCTs, and therefore individuals unfamiliar with this study design may consider first attending the Designing and Conducting Pragmatic Randomised Controlled Trials short course. Experience of having worked on an RCT would be particularly beneficial, although not essential. |
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Statistical Methods for Mediation Analysis
Please ensure you meet the following prerequisites before booking:
Knowledge |
Participants should have knowledge of regression analyses and their implementation in Stata of at least the level achieved in the Introduction to Linear and Logistic Regression Models short course. |
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Software |
You must have Stata* (version 14, 15, 16 or 17) installed in advance of the course. *Internal University of Bristol participants are given access to Stata. Go to Stata Installation Instructions (internal only) for help setting it up before the start of the course. External participants are responsible for providing their own access to Stata. |
Writing a Journal Article
Please ensure you meet the following prerequisites before booking:
Knowledge |
Candidates must have completed a piece of work and be ready to write it up. |
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Note: This is an internal course, available only to invited University of Bristol staff and students.
Writing a Qualitative Paper
Please ensure you meet the following prerequisites before booking:
Knowledge |
This course is only suitable for researchers who have already completed or are well underway with their qualitative data collection and analysis. If you are not yet at that stage please consider booking onto a later course. |
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Preparation |
In advance of the course please identify one or two published articles that you think are good examples of the kinds of qualitative writing that you aspire to. |
Note: This is an internal course, available only to invited University of Bristol staff and students.