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.
Registration deadline: 11 February 2024
Exam date: 2 May 2024
Why follow this online Master's course 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.
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. You will be able to apply statistical techniques to your work, make data-driven decisions, and ultimately contribute to the development of improved plant varieties.
Is this course for you?
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.
What you'll learn
After successful completion of this online course, 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;
- 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.
Study knowledge clips with theoretical assignments, practical assignments and a case study using R, reporting on results.
When enrolling in this course, you may apply for the use of the STAP budget. Check if you are eligible for the STAP-budget.
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).
Software used in this course
R including R studio.
This course is quite time-intensive and requires approximately 20 hours per week for the average participant. There are assignments with deadlines.
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.
You should have sufficient knowledge on concepts and methodologies related to plant biology, such as genetics, plant breeding, plant physiology and molecular biology.
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 this document.
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.
Upon successful completion, - 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.
More information & Registration
You can register for this course. Have any questions? Contact Wageningen Academy.