Our Stats Cadets support supervisors of the Department of Zoology in advising postgraduate students on study design, data management and statistical analysis.

Inquiry

Please first read the information on this site.

Send a project description to the Stats Programme Coordinator (Paul Szyszka), who will bring you into contact with the right Stats Cadet.

Level of support

For a given study, the Zoology Department will offer 3 hours of meeting for free. We recommend:

  • one hour meeting at the study design stage, planning of data collection and analysis, and
  • two hours meeting for help with data analysis. Stats Cadets may demonstrate but do not undertake analyses for the students.

Further meetings for the same study need to be payed by the student's or supervisor's budget.

Prerequisites for meeting a stats cadet

Prepare a project description with the following information:

  • specify what advice you need (e.g., experimental design, analysis, software, programming),
  • questions and/or hypotheses of your study,
  • experimental design (or a suggestion for it),
  • response variables and explanatory variables,
  • a suggestion for a meaningful visualization of your data, and
  • a suggestion for a strategy for data collection, management and analysis,
  • who is your supervisor.

If you seek advice for more than one study, prepare a separate project description for each study.

 

If you want to base your analysis on a published analysis, provide a link to that publication.

Send the project description via email to Paul Szyszka and in CC to your primary supervisor.

 

Roles of the student and supervisor

  • The supervisor will remain fully engaged throughout the project, and be kept informed by the student of all advice provided.
  • The supervisor should attend the first meeting.
  • OPTIONAL, at the supervisor's discretion: At the end of each meeting with a Stats Cadet, the student (in presence of the Stats Cadet) prepares a short report that answers the following questions:
  1. Which of your questions did this consultation answer?
  2. Which experimental design/statistical tests did you agree on?
  3. Which of your questions could not be resolved?
  4. How will you get help for the unresolved questions?
  • The student sends this report to Paul Szyszka and in CC to the supervisor.
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Stats cadets

Stefanie Neupert

Linear models, GLMs, Mixed effects models, Bayesian statistics.
Software: R

 


Scott Bourke

Experimental design, Data curation and exploratory analyses including work with flawed data, Power analysis, Linear models, GLMs, GAMs, Model selection and inference, Correlative Species distribution modelling using GAM, Maximum Entropy, and Random Forest algorithms, Mark-Recapture.

Software: R, QGIS 


Shar Mathias 

R solving errors and code problems, species distribution models especially MaxEnt, ANOVA, GLMs, and mixed effect models

Software: R 

 


Daniel Zamorano

ANOVA, GLM and GAM. Multifactorial analyses (PCA, RDA, CCA, NMDS). Permutation analyses. 

Software: R 

High quality plots in ggplot2. Broad experience in R, cleaning codes, solving "why this is not running" problems and automatizing processes. Also, experience developing apps via Shiny in R, doing cartography in R and Qgis and making R packages. 


If you need advice on other analyses, please contact the Stats Cadet Programme Coordinator (Paul Szyszka).

Do you want to become a stats cadet?

Stats Cadets are employed on a casual basis and are paid hourly.

Please contact Stats Cadet Programme Coordinator (Paul Szyszka)