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ONLINE COURSE – Statistical Radiocarbon Dating And Age Depth Modelling (RDAD01) This course will be delivered live
18th May 2022 - 20th May 2022
£400.00
Event Date
Wednesday, May 18th, 2022
Course Format
This is a ‘LIVE COURSE’ – the instructor will be delivering lectures and coaching attendees through the accompanying computer practical’s via video link, a good internet connection is essential.
Time Zone
TIME ZONE – Western European Time – however all sessions will be recorded and made available allowing attendees from different time zones to follow.
Please email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you.
About This Course
This course will provide attendees with the basics to understand and implement age-depth models for partially dated stratigraphic data. The focus will be on radiocarbon dating but the approach extends to many other forms of dated information, and will be relevant to those who have a wide variety of palaeo-environmental reconstruction problems. As is common in age-depth modelling, the Bayesian paradigm will be used to create the age-depth models, though no prior experience with Bayesian software or methods is required. The course will cover the use of multiple different R packages though the focus will be on the author’s own Bchron software. Attendees are encouraged to bring their own data sets and explore them using the tools covered during the course.
Intended Audiences
Venue
Delivered remotely
Course Details
Time zone – Western European Time
Availability – 30 places
Duration – 3 days
Contact hours – Approx. 21 hours
ECT’s – Equal to 2 ECT’s
Language – English
PLEASE READ – CANCELLATION POLICY: Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.
Teaching Format
A mixture of lectures and hands-on practicals. Data sets for computer practicals will be provided by the instructors, but participants are welcome to bring their own data.
Assumed quantitative knowledge
Basic knowledge of statistics and statistical models (e.g. generalised linear modelling) required. Basic experience of exploring data sets, and fitting regression and generalised linear models with R required.
Assumed computer background
Equipment and software requirements
A laptop computer with a working version of R or RStudio is required. R and RStudio are both available as free and open source software for PCs, Macs, and Linux computers. R may be downloaded by following the links here https://www.r-project.org/. RStudio may be downloaded by following the links here: https://www.rstudio.com/.
All the R packages that we will use in this course will be possible to download and install during the workshop itself as and when they are needed, and a full list of required packages will be made available to all attendees prior to the course.
A working webcam is desirable for enhanced interactivity during the live sessions, we encourage attendees to keep their cameras on during live zoom sessions.
Although not strictly required, using a large monitor or preferably even a second monitor will improve he learning experience
PLEASE READ – CANCELLATION POLICY
Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.
If you are unsure about course suitability, please get in touch by email to find out more oliverhooker@prstatistics.com
COURSE PROGRAMME
Wednesday 18th – Classes from 09:30 – 17:30
Day 1: Introduction to Radiocarbon dating; introduction to Bayesian statistics; basics of radiocarbon calibration
Thursday 19th – Classes from 09:30 – 17:30
Day 2: Methods for calibrating radiocarbon dating; introducing prior information into radiocarbon date; basics of age-depth modelling
Friday 20th – Classes from 09:30 – 17:30
Day 3: Age-depth modelling approaches (Bacon, Bchron, Clam, Oxcal); extending and using age-depth models in palaeo-environmental reconstruction
Course Instructor
Prof. Andrew Parnell
Works at –
Teaches –