R 4 ALL (Andrew Beckerman & Dylan Childs) (R4LL01) FREE ACCOMMODATION AVAILABLE
20th January 2020 - 23rd January 2020£275.00 - £550.00
PR Statistics has partnered with R4ALL (www.r4all.org) to offer an introductory course to R, RStudio and statistics for Biologists. Based on their best-selling book, “Getting Started with R, An Introduction for Biologists”, this course provides training in the R statistical and programming language for data management, visualisation, and analysis. The R4All team, with more than 20 years experience delivering this course, will boost you up the initial learning curve, streamline your data management and analysis workflows, and give you scalable solutions. You will develop and take away robust and repeatable workflows for visualisation and statistical analyses, ranging from t-tests and ANOVA to generalised linear models and mixed effects models.
The course is aimed at biologists with a basic to moderate knowledge in R and undergraduate biology statistics (ANOVA and regression). The course content is designed to bridge the gap between basic statistics and more advanced statistical modelling tools such as Generalised Linear Models and Mixed Models (Random Effects).
Venue – PR statistics head office, 53 Morrison Street, Glasgow, G5 8LB – Google Map
Availability – 20 places
Duration – 5 days
Contact hours – Approx. 35 hours
ECT’s – Equal to 3 ECT’s
Language – English
• COURSE ONLY – Includes lunch and refreshments.
• ACCOMMODATION PACKAGE (to be purchased in addition to the course only option) – Includes breakfast, lunch, refreshments and welcome dinner Monday evening. Self-catering facilities are available in the accommodation. Accommodation is multiple occupancy (max 3- 4 people) single sex en-suite rooms. Arrival Sunday 19th January (between 17:00-21:00) and departure Friday 24th January (accommodation must be vacated by 09:15).
To book ‘COURSE ONLY’ with the option to add the additional ‘ACCOMMODATION PACKAGE’ please scroll to the bottom of this page.
Other payment options are available please email firstname.lastname@example.org
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 email@example.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 (and accommodation fees if booked through PR statistics) will be credited. However, PR statistics will not be held responsible/liable for any travel fees, accommodation costs or other expenses incurred to you as a result of the cancellation. Because of this PR statistics strongly recommends any travel and accommodation that is booked by you or your institute is refundable/flexible and to delay booking your travel and accommodation as close the course start date as economical viable.
A mixture of lectures, hands-on practicals making graphs and doing analyses and Q&A sessions. Datasets for computer practicals will be provided by the instructors; participants are welcome to bring their own data.
Assumed quantitative knowledge
The course will be most effective if students are comfortable with basic statistics such as t-tests, regression and ANOVA. For example, this assumes they have some familiarity with 1) the difference between response and explanatory variables, 2) the residuals from a fitted statistical model, 3) standard errors and confidence intervals, 4) test statistics (e.g. t- and F-statistics).
Assumed computer background
Required: Ability to download files from the internet and organise folders and files on your computer.
Valuable, but not required: Using R via RStudio to create scripts, import/export data, generate simple exploratory plots and fit basic statistical models.
Equipment and software requirements
Students will use their own laptop. They must have administrative rights on the computer. They should have installed the latest version of R (free) and RStudio (free). Installation instructions for all platforms can be found on CRAN and the RStudio download pages. No other software is required.
UNSURE ABOUT SUITABLILITY THEN PLEASE ASK firstname.lastname@example.org
Meet at Flat 2/1, 43 Cook Street, Glasgow G5 8JN between 17:00-21:00
Monday 20th – Classes from 09:30 to 17:30
Day 1 – Import, Explore, Graph
Topic 1 – Why R? Why use the ‘tidyverse’?
Topic 2 – Data import, cleaning and manipulation with dplyr
Topic 3 – Data exploration and visualisation with ggplot2
Tuesday 21st – Classes from 09:30 to 17:30
Day 2 – Revising basic statistics and linear models
Topic 1 – Basic statistics revision
Topic 2 – Simple linear models (regression and ANOVA)
Topic 3 – Model diagnostics for linear models
Topic 4 – More complex linear models
Wednesday 22nd – Classes from 09:30 to 17:30
Day 3 – Generalised linear models (GLMs)
Topic 1 – Basic concepts underlying GLMs
Topic 2 – Working with Poisson models
Topic 3 – Model diagnostics and p-values for GLMs
Topic 4 – Working with Binomial models
Thursday 23rd – Classes from 09:30 to 17:30
Day 4 – Mixed effects models and miscellany
Topic 1 – Basic concepts underlying mixed models
Topic 2 – Understanding model syntax using lme4
Topic 3 – Adapting the workflow for mixed models
Topic 4 – p-values with mixed models
Friday 24th – Classes from 09:30 to 16:30
Day 5 – Bring your own data workshop AND/OR assorted topics chosen by class.
The instructors were excellent and clearly were the reasons for my previous comments. They both combined a deep understanding of statistics and ecology at the same level.Any questions or queries I’ve had, were thus first answered with an ecological point of view and then translated into statistical consideration thereby making much more sense on both side.In addition the course was very well organised, the course director and the two instructors were very friendly as well as professional. On the top of learning many useful things, I’ve also had a very good time during the week there.” Clement Garcia,
Spatial ecologist, Centre For Environment, Fisheries & Aquaculture Science (CEFAS), England
(Attended ADVR course)