PSI Tutor: Academic Mentor

A measure of central tendency is a statistics phrase that could be a Buddhist metaphor as to how to live life:

take heed of the middle way

Behaviours-thoughts-affects tend to cluster at the centre of a persons character, to act as a fulcrum to decision-making and responses within an environment.

In psychology, statistics identify behaviors-thoughts-affects that are central to a group of people, known as a population.

This post will give you three benefits as a psychology undergrad;

• understanding one “measure of central tendency“
• practice using math formula
• greater confidence talking about, reading about and thinking about the mean (one measure of central tendency)

There is a semantic difference between the “average” and the “mean”. The average can be any measure of central tendency (e.g., median, mode, geometric mean, weighted mean); the mean is one example of a measure of central tendency.

Choosing a measure of central tendency to observe/report depends on what you are measuring (e.g., eye colour, number of smiles in 5-minutes, student rankings of a tutors skills). When measuring continuous numbers, such as the number of smiles in 5-minutes, the mean can provide a lot of information.

Finding the mean: M = ΣX/N

1. Sum all the scores

2. Divide by the number of scores

e.g., number of smiles in 5-minutes of people in tutorial; 0, 2, 2, 5, 1, 1, 3, 4, 2, 1, 0, 0, 4

1. 0+2+2+5+1+1+3+4+2+1+0+0+4 = 25

2. 25 /13 = 1.9 smiles in 5-minutes per student in this tutorial is the mean

What does this mean, mean? That, on average, during this tutorial, each class member smiled 1.9 times. The relevance of the mean will depend on the research question. Why were smiles in a psychology tute being measured in the first place?

As it happens, it was a first year stats class, and the tutor as a post-grad is doing his Master’s research on the state of Happiness and the effects on Learning Ability. The tutor used his literature review to identify what measure of central tendency had been used in other research on the topic. The first three weeks of tutes provide the baseline data for the mean number of smiles per class. The tutor will then use a self-developed method to facilitate learning which is expected to enhance feelings of happiness amongst students, and so enable them to learn more effectively. Number of smiles in a 5-minute period one of the dependent variables for the study. Time before, during and after the intervention is the independent variable. To determine if there really is a change in smiling behaviour made by the intervention (between times/groups) the mean is needed.

However, the most frequent score was “0″, so the mean can be misleading if the range or standard deviation are not shown as well (for another post). For this reason three weeks of baseline data were collected to compute one overall mean of number of smiles in a 5-minute period (week 1 mean+week 2 mean+week 3 mean/3 = ?.?).

The mean goes beyond just describing data, and provides a value that can be used to make inferences about the likelihood of events occurring, the degree of risk, or the strength of a relationship between variables, for example. Statistical tests such as t-test, factor analysis and multiple regression rely on the mean for a measure of central tendency.

An interesting tangent on this subject is that the mean of a population is called mu (µ), the term in Zen Buddhism referring to being and non-being simultaneously. A population does and does not exist! A population only exists in terms of the group of characteristics a researcher decides will be used to describe it. How serendipic~