Workshop at CES on 10 January 2020 at 10:00 am titled "Advanced Statistics Workshop 2020 (Open for selected participants only)" by Prof Nagaraja and Dr Kavita Isvaran from The Ohio State University and CES
These workshops are intended to serve as an introduction/refresher to commonly used advanced statistical models. The workshops will consist of lectures on how the different statistical models work, accompanied by hands-on sessions in R, where we apply these models to ecological data-sets and become familiar with fitting and interpreting them.
The detailed schedule for the workshops is available here:
https://docs.google.com/document/d/1h6dCLtXBxTRhVi4_MV-3VOLTREP9AcRa81of...
Topic 1: Generalised Linear Models (GLM)
10th January (Friday) 10am - 1pm: Discrete data problems - Prof Nagaraja
13th January (Monday) 10am - 1pm: GLMs with examples of binary and proportion data - Prof. Nagaraja
14th January (Tuesday) 10am - 1pm: R Session: Applying GLMs to ecological data sets - Kavita
(15th Jan 2020 is a HOLIDAY)
16th January (Thursday) 10am - 1 pm: GLMs with examples of count data - Prof. Nagaraja
17th Jan (Friday) 10am - 1pm: R Session: Applying GLMs to ecological data sets - Kavita
Topic 2: Mixed-effects Models
27th Jan (Monday): 10am - 1pm: GLM With examples of zero inflation + R session (by Prof Nagaraja)
28th Jan (Tuesday): 10am - 1pm: Linear mixed-effects models - Prof. Nagaraja
29th Jan (Wednesday): 10am - 1pm: R Session: Applying LMMs to ecological data sets - Kavita
30th Jan (Thursday): 10am - 1pm: 11th Jan 10am - 1pm: Generalised Linear Mixed-effects Models GLMMs - Prof. Nagaraja
31st Jan (Friday): 10 am - 1pm: R Session: Applying GLMMs to ecological data sets - Kavita
*Attendance only with Registration.
**Pre-requisites: Since these workshops focus on advanced statistical models, familiarity with basic statistics (statistical hypothesis testing, one and two-sample problems, simple linear regression, one-way ANOVA) and basic math and probability (functions, distributions) is expected. Since we will be working in R/RStudio, some familiarity with R & R-studio is also expected.