5. Type 1 and Type 2 Errors

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About this Lecture

Lecture

In this lecture, we think about type 1 and type 2 errors, focusing in particular on: (i) contextualising the afore discussed 0.05 p-value, or 5% probability; (ii) outlining under which circumstances of null hypothesis status and effect presence that each of those two errors would arise, and where the correct decisions would be being made (iii) bringing these considerations into the light of real research by considering the consequences of each error type under certain circumstances.

Course

In this course, Dr Alison Wadeley (Bath Spa University) explores the challenging subject of inferential statistics. In the first lecture, we think about the decision tree required to establish which non-parametric test should be used, based on the experimental design and the data being collected. In the second lecture, we think about four example research questions and work through the process of deciding which non-parametric test is appropriate for each, before moving on to parametric tests. In the third lecture, we think about how the sign test is used to assess a research question on sleep quality and social media use. Next, we think about probability, critical values, and significance; helping to unpack the inner workings of these tests. In the fifth and final lecture, we think about the errors that can occur when interpreting results from these tests, how you might recognise them, and what can be done to reduce their prevalence.

Lecturer

Dr Alison Wadeley is a senior lecturer in the Department of Psychology at Bath Spa University, leading undergraduate teaching on psychological research methods and statistics. Dr Wadeley’s own research focuses on how naturally occurring sleep disruption can impact adult cognitive function, as well as ankylosing spondylitis. Dr Wadeley’s recent publications include ‘Real-world experience of secukinumab treatment for ankylosing spondylitis at the Royal National Hospital for Rheumatic Diseases, Bath’ (2020) and ‘Does measuring the bone mineral density of patients identified as having an osteopaenic X-ray appearance affect bone health treatment decisions? A real-world retrospective analysis’ (2019).