The Mean and Standard Deviation

About the lecture

In this lecture, we think about the arithmetic mean and the standard deviation, focusing in particular on: (i) defining the mean as the sum of all of the scores in the dataset, divided by the number of scores in that dataset; (ii) the susceptibility of the mean to outlying data points; (iii) the advantage and disadvantage of being sensitive to extreme scores; (iv) the fact that the mean score does not necessarily exist within a dataset of score, meaning that it is not strictly a ‘typical’ score; (v) defining the standard deviation as the average deviation from the mean; (vi) overcoming the problem of the average deviation from the mean always equalling zero, by squaring the values within the standard deviation calculation; (vii) the limitation of the mean as only working with interval level data or above, as it requires adding scores together.

About the lecturer

Professor Dominic Dwyer is the chair for the BSc and MSc exam boards in the School of Psychology at Cardiff University. Professor Dwyer teaches introductory statistics for undergraduate years one and two. Professor Dwyer’s research is primarily focused on how animals and people learn, as well as how that learning is expressed as behaviour. Some key focus areas of this research are computational modelling, neurodegenerative disorders, and the assessment of individual differences. Some of Professor Dwyer’s recent publications include 'EXPRESS: Instrumental responses and Pavlovian stimuli as temporal referents in a peak procedure' (2022) and 'Face masks have emotion-dependent dissociable effects on accuracy and confidence in identifying facial expressions of emotion' (2022).