VET414 Applied statistics for experimental and laboratory oriented studies in veterinary science
Showing course contents for the educational year 2021 - 2022 .
Course responsible: Janicke Nordgreen
Teachers: Andrew Michael Janczak, Preben Boysen, Eystein Skjerve
ECTS credits: 5
Faculty: Faculty of Veterinary Medicine
Teaching language: EN, NO
Teaching exam periods:
Week 38-46. One meeting each week and an oral exam week 46.
Course frequency: Yearly.
First time: Study year 2016-2017
The main goal of the course is to familiarize the students with central themes in applied statistics for experimental and laboratory-oriented studies in veterinary science. We introduce the students to sample of the following topics. The students will contribute to defining the exact content of the course.
Topics may include:
- Critical reading from an experimental design and statistical perspective.
- Aims of the study including hypothesis testing, descriptive and exploratory approaches.
- Links between aims and organization of the dataset and statistics.
- Designing experiments.
- Software based Design of Experiments (DOE).
- Power and sample size estimation.
- Databases, structure and establishment.
- Outcome variable(s) and links to analytical model.
- General Linear Models (GLM) and Analysis of Variance (ANOVA).
- Nesting and repeated measures designs.
- Regression Analysis.
- Non-parametric statistical tests.
- Presentation of data.
- Use of Excel for organizing data.
- Descriptive data analysis using pivot functions in Excel.
- Use of the statistical software package JMP for data analysis.
Through the course the students are expected to achieve the following:
- The students will develop their ability to plan their own studies and analyze their own data.
- Know the main principles of applied statistics.
- Know the standards for planning, analyses and presentation of data for scientific publishing in their research area.
- Be able to design a study based upon statistical principles.
- Be able to organize data using Excel and analyse data using JMP.
- Be able to perform basic statistical analysis of dataset, according to needs in own dataset/study.
- Be able to communicate about statistics in order to continue to develop skills and understanding after the course has finished.
- The students should develop attitudes in line with acceptable research ethics in connection with statistical analysis.
The course is a mix of lectures, demonstrations, assignments and group discussions.
- Grafen & Hails: Modern Statistics for the Life Sciences 1 edition (2002). Oxford University Press, UK. 368 pages.
- Petrie and Watson: Statistics in veterinary and animal science, 3rs edition (2013). John Wiley & Sons, UK. 408 pages.
- Alex Reinhardt: Statistics Gone Wrong: The Woefully Complete Guide, 1st Edition (2015). No Starch Press, San Fransisco, USA. 176 pages.
Further material will be handed out during the course.
The course aims at introducing statistics to PhD students with a veterinary or other biological background, and veterinary research track students. Only minimal prior statistical knowledge is expected.
Attendance and preparation for classes through reading and exercises is compulsory. An attendance record of at least 70% is required to pass this course. Exceptions will be considered for students following the course over more than one semester.
Weekly assignments followed by oral exam.
A2: no calculator, other specified aids.
Mandatory enrolment via Student web (1st of September)
Examination details: Anvendt statistikk for eksperimentelle- og laboratoriestudier i veterinærvitenskap: Passed / Not Passed