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3. The Median

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About this Lecture

Lecture

In this lecture, we think about the median, focusing in particular on: (i) calculating the median for datasets with both odd and even total numbers of data points; (ii) the property of the median to demonstrate not only the central tendency, but also to precisely highlight the actual centre point of the dataset; (iii) the influence of skewness in a dataset on different measures of central tendency, with the example of income, which has a minimal impact on the median value; (iv) range as a tool used to assess the dispersion of data that can be paired with the median score to indicate the representativeness of that score; (v) the susceptibility of the range to outlying scores.

Course

In this course, Professor Dominic Dwyer (Cardiff University) explores descriptive statistics. In the first lecture, we think about why descriptive statistics are important. In the second lecture, we think about the mode and its representation of the most common score. In the third lecture, we think about the median and how it is only minimally sensitive to outlying scores. Next, we think about the mean and standard deviation, exploring how to calculate each one. In the fifth and final lecture, we think about how these different measures of central tendency and dispersion can be appropriate for different datasets.

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).