Plant Breeding: Advanced Statistics

Welcome to our comprehensive course on statistics! This course has been designed specifically for professionals who want to enhance their knowledge and skills in the field of statistics. Through this course, you will gain a deep understanding of the most important statistical concepts and methods used in plant breeding. You will learn how to collect and analyse data, how to interpret statistical results, and how to make data-driven decisions.

Organised by Wageningen Academy

Mon 7 April 2025 until Fri 2 May 2025

Duration 4 weeks (20 hours per week)
Price EUR 1,230.00

Registration deadline: 10 February 2025

Please note that the dates for the academic year of 2024-2025 are yet to be confirmed, so they might still change.

Target audience

If you are a working professional in the plant breeding sector, this course is the perfect opportunity for you to expand your knowledge and sharpen your skills. This comprehensive course will provide you with the tools you need to succeed and advance in your career, especially in combination with other advanced Online Master's Courses Plant Breeding.

Are you planning to join one of the Online Master's courses Plant Breeding or one of the Online Master's course series Plant Breeding, but lack statistical knowledge? Join this course first and ensure you have the right knowledge and skills for the other advanced plant breeding courses.

Prerequisite knowledge
You should have sufficient knowledge on concepts and methodologies related to plant biology, such as genetics, plant breeding, plant physiology and molecular biology. It's important to realise that, if you do not comply with these recommendations, you cannot claim extra support from the instructor and cannot claim a refund of the registration fee, if you decide to discontinue the course.

Learning outcomes

After successful completion of this programme, you will be able to:

  • Comprehend basic ideas of statistical inference, experimental design and data collection, such as random sampling, randomisation and blocking, for experimental and observational studies.
  • Apply statistical techniques to your work, make data-driven decisions, and ultimately contribute to the development of improved plant varieties.
  • Determine an appropriate statistical model and associated statistical inference procedure, given the description of the experiment and research question, for continuous data (in the context of linear regression, analysis of (co)variance) and discrete data (in the context of goodness-of-fit and contingency tables for categorical data and logistic regression for binary data and proportions).
  • Carry out the analysis, for a given problem, using the statistical program R, check model assumptions, interpret results, and formulate conclusions in terms of the actual problem.


This course covers statistical design and analysis of data using R; statistical methods for analysis comprise simple and multiple regression, one-way and two-way analysis of variance (with and without interaction), analysis of covariance, chi-square tests for contingency tables, and logistic regression. By the end of this course, you will have the skills and knowledge required to become a proficient plant breeding statistician.

This course is an online course at master level that you follow in a cohort. Learners participate at different time points and from different time zones, as most learners also have a job. The programme therefor offers learning activities that allow you to supervised self-study at your own pace, with deadlines for assignments, and includes knowledge clips, e-learning modules, online individual and group exercises and assignments, online discussions, and in some courses occasionally live question hours through MS Teams at specific dates and times. There are no online live classes. The exam has a fixed date.
The course a case study using R, reporting on results.

Literature used in this course:
Ott, RL, Longnecker M (2016), An introduction to statistical methods and data analysis (7th edition), Brooks/Cole ISBN-13 978-1-305-26947-7 (not included in the course fee).

This course is quite time-intensive and requires approximately 20 hours per week for the average participant. There are assignments with deadlines.

Software used in this course: R, including R studio.

Self-Paced Online Course Getting Started with R
You need to have a good basic understanding of statistics and you need to have experience with software ‘R'. If the latter is not the case, you can follow the Self-Paced Online Course Getting Started with R first. For more information and registration, please check the document linked in the right-hand column.


Participation in the remotely proctored exam is optional. If you decide not to participate in the exam, you do not qualify for a certificate and/or micro-credentials.

The date of examination is 01-05-2025 (1 May 2025). The duration of an exam is 3 hours. The resit will be scheduled in the week of 7 July 2025.


Upon successful completion (i.e. passing the exam and making assignments), a digital certificate with 3 study credits (ECTS) is issued. This certificate offers no immediate rights to apply for a formal degree programme at a university, but it might support your request for admission. In case you've also completed the Online Master's Course Experimental Design & Data Analysis of Breeding Trials successfully, you can obtain a micro-credentials certificate.

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Join this course now.