The scientific method is central to experimental research. It provides a suite of tools that allows us to gain knowledge of the world from acquired data. It is only via the interpretation of what the data means that we are able to make any meaningful conclusions about the real world.
Statistics describes the process of drawing conclusions from data and understanding the uncertainty of those conclusions. Seen in this light, statistics is essential to every stage of the scientific method - from collecting and describing data to inferring something about the real world. Unfortunately, it is often misunderstood and misused.
The often over-heard question “What test should I use?” reflects a poor understanding of statistics as a static & authoritative black box that is applied after results are obtained. It is essentially statistical illiteracy, a failure to properly understand and use statistics as a part of scientific inquiry. The Statistical Literacy workshop aims to provide the foundation to become statistically literate.
This is similar to how an experimental biologist needs to have an intuitive feel for the nuances of an experimental method. Without understanding the limitations of a method, results cannot be properly interpreted; nor can problems be identified and resolved. Results are accepted at face value without considering where they come from.
It is a fairly intense workshop! It’s more important that you improve your understanding of statistics instead of just having as much material as possible covered in three days. Therefore, treat the workshop outline as a guide only. Depending on the pace of the class, some advanced topics may not be covered.
The workshop material has been prepared with a great amount of input from Irina Czogiel, who holds a PhD in statistics and currently works for the German Ministry of Health.
The workshop consists of three sections: Collecting, Describing & Inferring. Practical tools and the theoretical background to understand how they work will be introduced. Mathematical equations will be used when helpful and are provided in the reference book, but they will not be the focus of the workshop. Our goal is to enlighten via intuitive understanding, not confuse via math.
A short list of workshop topics is provided below.
There are no prerequisites for this workshop. It is intended for young doctoral students in the life sciences and assumes no prior experience in statistics.
This workshop is targeted towards early-stage doctoral students in the life sciences. It is not possible to cover all aspects of statistics in two days, nor go into a deep discussion of specific topics. Rather, this workshop is meant as a refresher for university-level introductory statistics courses. It is not a comprehensive survey of all techniques students may encounter, nor is it a custom consultation service to advise students on their specific research questions.
The tentative schedule for each day is:
You are expected to attend the entire workshop. Thus, please set aside any other commitments you have during this these days.
Please contact your coordinator for the location.