2  Learning Objectives

After this workshop, students should be able to…

  1. Understand and explain the relationship between measurements, statistics, and experimental design.
  2. Understand and explain that statistical models are devices that process data to produce estimates that support scientific insight.
  3. Understand how assumptions and expectations about the factors influencing an experiment can be translated into an effective experimental design.
  4. Use g*Power to estimate a group size for a statistical test.
  5. Use the NC3Rs Experimental Design Assistant to lay out and analyse a simple experiment, and export the design information.
What this workshop is

This workshop is an introduction to…

  1. the way your data collection is subject to factors that affect all measurements
  2. how the biological or physical process you are studying affects the data you collect
  3. making assumptions about causal factors in your data explicit
  4. using experimental design to improve data collection, exclude influences you are not scientifically interested in, and minimise the number of experimental subjects required to test a model
  5. how to use the NC3Rs Experimental Design Assistant (EDA) to lay out and analyse an experimental design
What this workshop is not
  1. Yet another introduction to t-tests, means, and standard deviations
  2. A guide to how you should design or analyse any specific experiment
  3. Advocacy for any particular statistical method, software, or tool
  4. An exhaustive presentation of statistics or training in statistical methodology