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ONLINE COURSE – A Non Mathematical Introduction To Ordination Methods Using R (ORDM01) Registration deadline 27th February – This course will be delivered live

27 March 2023 - 30 March 2023

£400.00
ONLINE COURSE – A Non Mathematical Introduction To Ordination Methods Using R (ORDM01) Registration deadline 27th February – This course will be delivered live

Event Date

Monday, March 27th, 2023

COURSE FORMAT

This is a ‘LIVE COURSE’ – the instructors 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 – EST – 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 introduce you to the main methods of both constrained and unconstrained ordination without entering into the mathematical details of these methods. The following methods will be studied: principal component analysis; correspondence analysis and its detrended version; principal coordinates analysis; metric and non-metric multidimensional scaling; redundancy analysis, canonical correspondence analysis; gradient analysis using siteXspecies data.

By the end of the course, participants should be able to:

  • Understand how each method works and the assumptions inherent in each;
  • Choose the most appropriate method relative to their data and goals;
  • Carry out the analyses in the R statistical environment
  • Interpret their results
Intended Audiences
  • Graduate or post-doctoral level researchers who wish to learn how to perform ordination techniques in R;
  • Applied researchers and analysts in the environmental/ecological sector with a role in handling and analysing data
Venue

Delivered remotely

Course Details

Time Zone – EST

Availability – TBC

Duration – 4 days

Contact hours – Approx. 30 hours

ECT’s – Equal to 3 ECT’s

Language – English

Teaching Format

This course will comprise a mixture of taught theory and practical examples. Data and analytical approaches will be presented in a lecture format to introduce key concepts. Statistical analyses will then be presented using R. All R script that the instructor uses during these sessions will be shared with participants, and R script will be presented and explained.

Ideally, participants will be able to use a computer screen that is sufficiently large to enable them to view my shared RStudio and their own RStudio simultaneously.

Assumed quantitative knowledge

I assume that participants have a basic knowledge of general statistical concepts and of linear models.

Assumed computer background

Experience with performing statistical analyses using R and R Studio will be assumed.

Equipment and software requirements

A computer with the most recent version of R and RStudio is required. R and RStudio are both available as free and open source software for PCs, Macs, and Linux computers.

A full list of required packages will be made available to participants prior to the course.

Ideally, participants will be able to use a computer screen that is sufficiently large to enable them to view my shared RStudio and their own RStudio simultaneously.

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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

Monday 27th
Day 1 09:00 – 16:00


Principal components analysis (PCA)

  • A graphical explanation of how PCA works
  • Data preparation and basic assumptions
  • Dealing with proportions
  • Using a covariance matrix or a correlation matrix?
  • Steps in fitting a PCA
  • Evaluating the importance of each axis
  • Relating variables to the axes
  • Relating observations to the axes
  • Choosing which axes to use
  • Graphical visualizations using biplots
  • Correspondence analysis (CA) & detrended correspondence analysis (DCA)

  • Direct gradient analysis in ecology
  • CA as a form of direct gradient analysis
  • Steps in fitting a CA
  • Bias due to the “arch effect” and its correction by detrending
  • An empirical example
  • Interpreting the output and graphical presentation
Tuesday 28th
Day 2 09:00 – 16:00

Principal coordinates analysis (PCoA)

  • Distance and dissimilarity measures
  • Measures for nominal categorical, binary, ordinal and quantitative variables
  • Gower’s distance
  • PCA and CA as special cases of multidimensional scaling
  • A graphical explanation of how PCoA works
  • Steps in fitting a CA
  • Performing PCoA in R
  • Metric (MDS) and non-metric multidimensional scaling (NMDS)

  • What is multidimensional scaling and how does it work?
  • What is non-metric multidimensional scaling?
  • Performing NMDS in R.
  • Graphical methods for evaluating and interpreting NMDS results
  • Procrustes analysis
  • An empirical example
Wednesday 29th

Day 3 09:00 – 16:00

Constrained ordinations

  • Exploratory vs. inferential statistical methods
  • Redundancy analysis (RDA)
  • Obtaining output from rda()
  • Hypothesis testing with rda()
  • Partial RDA
  • Canonical correspondence analysis (CCA)
  • Partial CCA
  • Hypothesis testing with CCA
  • Distance-based redundancy analysis (db-RDA)
  • Empirical example
  • Thursday 30th

    Day 4 09:00 – 12h00

  • Gradient analysis using siteXspecies data
  • Simulating environmental gradients
  • Using simulations to compare ordination methods
  • The “horseshoe” or “arch” effect
  • Flexible shortest path adjustments
  • Recommendations for siteXspecies ordinations
  • Implications for constrained ordination methods
  • Course Instructor

    Prof. John (Bill) Shipley

    Bill Shipley is an experienced researcher and  teacher in plant ecology and statistical ecology. He has published four scientific monographs and over 170 peer-reviewed papers.

    Details

    Start:
    27 March 2023
    End:
    30 March 2023
    Cost:
    £400.00
    Event Categories:
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    Tickets

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