Course overview

Be it in bioscience or business, if you want to use data to help guide a given enterprise, you need to understand statistics and experimental design. The Statistics and Experimental Design for Bioscientists course that helps you engage with that data. It will explain the major principles and techniques of statistical analysis of research data without becoming too involved in the underlying mathematics.

Now that computer software is very well established for data analysis, it is more important to understand WHAT a statistical test is doing (and thus whether or not it is appropriate) than to be able to perform the underlying calculations by hand. It is equally important to collect data in an appropriate and planned manner for later analysis.

Part of studying statistics is using data to develop hypotheses that can be tested with experiements, which managers can use to develop a plan a course of action from or with data. These techniques would be helpful for those working with an around management. Because of this, the Statistics and Experimental Design for Bioscientists course would be suitable for people who works in or around management looking for postgraduate study.

At the end of the course, participants should have an overall grasp of the major analytical techniques available, and how they relate to each other, and have developed abilities in experimental design, data analysis using appropriate software and presentation of results.

Learning outcomes

You will gain knowledge and understanding of:

  • The major analytical techniques available
  • The principles of experimental design and major approaches to statistical data analysis.

By the end of this course you will be able to:

  • Interpret data, critically appraise designs and analyses by peers.
  • design experiments, organise, analyse and interpret data, write reports, assess evidence and produce concise reports.
Additional Course Information

Areas covered on this course will include:

  • Introduction to statistics
  • Linear Regression
  • ANOVA, ANCOVA, Multiple Regression, Log-linear & Logistic analysis
  • Introduction to GenStat: Regression, ANOVA, ANCOVA in Genstat
  • How to, and not to, present results of statistical analyses
  • Experimental design simulation exercise: design an experiment and use a simulation model to generate data.

    Key facts

    Course Dates
    The course will commence with an introduction to statistics through e-learning. This preliminary study will provide the foundation for the five day intensive course. The course can be taken as a stand-alone training course but is also the one compulsory unit of the MSc in Agrifood.
    Entry Requirements
    Graduate level or experience within the agrifood industry
    IFST Membership
    Your course enrolment also entitles you to one year of free membership to the IFST (Institute of Food, Science and Technology).
    Course Provider
    University of Nottingham
    Provider Reference Number
    Course Arrangements
    Full joining instructions will be confirmed by the course provider.
    Course Location
    Online, University of Nottingham
    AFTP Cohort
    Course Logistics
    Lunch is provided.
    My AFTP training course has given me greater confidence day-to-day and more insight into the impact of new techniques and technologies.
    Andy Russell - Fresh Produce Technologist, Bakkavor

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