Statistics and Experimental Design for Bioscientists
| Code | School | Level | Credits | Semesters |
| BIOS4001 | Biosciences | 4 | 10 | Autumn UK |
- Code
- BIOS4001
- School
- Biosciences
- Level
- 4
- Credits
- 10
- Semesters
- Autumn UK
Summary
Handling data in the open-source R environment. Design of experiments and sample surveys. Data exploration and visualisation. Testing hypotheses with data, including those from various designed experiments. Regression analysis and its applications.
Target Students
MSc/PGDIP Crop Improvement, PGR/PGT Agrifood, MSci in Animal Science,Biotechnology Environmental Science, Environmental Biology, Food Science, Food Science and Nutrition,Natural sciences, Nutrition, Plant Science, students.
Classes
- One 3-hour lecture each week for 11 weeks
One half day per week throughout the semester to include lectures and practical computing classes. Tutor led (30 hours), course work (25 hours), revision 20 hours, (total 75 hours).
Assessment
- 100% Coursework 1: 100% Coursework
Assessed by end of autumn semester
Educational Aims
Participants should develop an understanding of the role of statistics in the biosciences and how scientists and statisticians collaborate. They should understand the importance of sound design, both of experiments and of surveys, and should be familiar with the methods used to analyse data from the principal designs. They should be familiar with the R environment, and able to use it to implement the analyses that are included in the course.Learning Outcomes
On completion of this module, students will be able to:
- Load data into the R environment and use R functions to explore and analyse them.
- Explain how statistical analysis enables bioscientists to draw sound inferences from data.
- Design basic experiments or sample surveys, and manage, explore, analyse the resulting data.
- Communicate the results of a statistical analysis with appropriate graphs and tables and make a sound biological interpretation of them.
- Critically review the statistical treatment of data in biological studies