Target audience: Early career researchers, especially PhD students and postdocs working in science, including vector-borne and other infectious diseases and ecology.

Tutors: Dr. Mafalda Viana and Dr. Abdelkader Behdenna (University of Glasgow, UK).

Supportting tutors: Dr. Athanase Bodolo (University of Ouagadougou, Burkina Faso) and Dr. Charlotte Payne (University of Cambridge, UK) and Dr. Luca Nelli (University of Glasgow, UK)

Duration: 1 or 2 weeks.

Number of participants: We are accepting 40 participants for week 1 and 10-12 participants for week 2.

Registration deadline: 08 October 2017

*** French version below ***

Course content:

Week 1 (20th-25th November 2017): Basic data visualisation and statistical analysis using R.

During this week, you will learn how to analyse data both from field collections and laboratory experiments. The week will comprise a mixture of lectures on data and statistical theory and hands-on exercises with R. Specifically,

• Day 1: Types of data and data presentation (am) + Introduction to R and plotting with R (pm)

• Day 2: Distributions & Likelihood (am) + Practical on distributions (pm)

• Day 3: GLMs (am) + Practical on GLMs (pm)

• Day 4: Poisson GLM + model selection (am) + Practical on poisson GLM and model selection (pm)

• Day 5: GLMMs (am) + Practical GLMM (pm)

• Day 6: Results presentation (am) + group tour (pm)

Week 2 (27th November - 1st December 2017): Analyses of your own data.

• This is an opportunity to analyse your own data with help of experienced quantitative ecologists/epidemiologists. During these 5 days you will work full time on your own project and we will be there all day to answer your questions about statistical analysis, coding in R, plotting the data etc. So that we can effectively help you, for this week, we ask you to bring your data and a question to address with those data. See below the pre-requisites for this week.

Pre-requisites:

Week 1: There are no pre-requites for the first module. We assume no prior knowledge of R or statistical analysis. However, we ask you to bring a laptop with the latest version of R or RStudio installed. If you don't have a laptop, please let us know in the application form and we will do our best to make one available for you.

Week 2: You will need basic R and statistical analysis knowledge (e.g. as acquired during week 1 or other course). In addition, you need to have your own data and a question you would like to address with those data. You will be asked details about this in the application form.

- All applicants must provide a reccommendation letter from their supervisor/line manager to attend the workshop. This letter should be sent by email to: bf.workshop2017@gmail.com.

Application details:

Applicants can choose to register for both weeks or just one week (please see pre-requisites for week 2). To apply click on the 'Register' button above and fill in the application form. Don't forget to email us your supervisor's reccommendation letter. While we hope to accept as many applicants as possible, there are limited spaces. Acceptance to the course will be mainly based on your motivation. You will have the chance to state your motivation in the application form. We aim to review all applications and confirm your place in the course by mid October 2017.

We accept and encourage applications from all African countries, however, we will give priority to Burkinabes for week 2. Week 1 will be for international students also.

Registration fee: There is no registration fee. In addition, we provide course materials and lunch for the duration of the course. However, you must make your own travel and accommodation arrangements.

Bursaries: We can offer accommodation to maximum 10 international participants in basic student accommodation. If you would like to be considered for this, please indicate your preference in the application form. Note, that this is for accommodation only, travel to and from Ouagadougou is the responsibility of the participant.

Other details: The course and course materials will be in English. However, support in French will be available. If you have any queries please contact us by email: bf.workshop2017@gmail.com.

Funders

This workshop is mainly supported by the UK Medical Research Council (fellowship no. MR/N015320/1). Support is also available through The Leverhulme Trust (grant no. RPG-2015-259) and MiRA project from Wellcome Trust [200222/Z/15/Z].

*** French version ***

Contenu du cours et prérequis

Semaine 1 : Analyse et visualisation de données obtenues sur le terrain ou en laboratoire à l'aide de R. La semaine sera partagée entre des cours portant sur les données et la théorie statistique d'une part, et des exercices pratiques sur R d'autre part.

Aucun prérequis pour cette semaine. Idéalement, apportez un ordinateur portable (avec R et/ou RStudio). Si vous ne pouvez pas, précisez-le dans le formulaire d'inscription, nous ferons notre possible pour vous en fournir un.

Semaine 2 : Analyse de vos propre données, avec l'assistance d'écologues/épidémiologistes expérimentés. Durant ces 5 jours, vous travaillerez sur votre propre projet et nous seront présents pour répondre à vos questions à propos de l'analyse statistique, la programmation sous R, la visualisation des données, etc. Nous vous demandons pour cette semaine d'apporter vos données et une/plusieurs problématique(s) liée(s) à ces données.

Vous aurez besoin de connaissances basiques sur R et l'analyse statistique (par exemple obtenues lors de la première semaine de ce workshop). Plus de détails à propos de vos données vous seront demandés dans le formulaire d'inscription.

Détails pratiques

Vous pouvez vous inscrire pour les deux semaine, ou seulement l'une d'entre elles (notez les prérequis pour la deuxième semaine), en cliquant sur "Register" puis en remplissant le formulaire d'inscription. Dû au nombre de place limitées, la sélection pour ce cours sera principalement basée sur vos motivations. Nous prévoyons de traiter toutes les demandes et donner une réponse à la mi-Octobre 2017.

Frais d'inscription : Le cours est gratuit (hors frais de déplacement et de logement).

Bourse : Nous pouvons loger jusqu'à 10 étudiants en logement étudiant. Vous pouvez postuler à une place au moment de remplir le formulaire d'inscription. Notez que cela ne concerne que le logement, et pas les frais de déplacement vers/depuis Ouagadougou.

Langue : Le cours sera donné en Anglais, avec une assistance en Français si nécessaire.