Doing Quantitative Research in Education with SPSS by Daniel Muijs
Author:Daniel Muijs
Language: eng
Format: epub
Publisher: Sage Publications
Published: 2011-03-10T16:00:00+00:00
6.8. Further reading
Any basic statistics text will contain a section on measures of central tendency and spread. For a more mathematical treatment than we have given here, the following text is a good one: Wonnacott, T. J. & Wonnacott, R. J. (1990), Introductory Statistics (Wiley).
Another good introduction is given in Aliaga, M. & Gunderson, B. (2002), Interactive Statistics (Prentice-Hall).
7
Bivariate analysis: comparing two groups
7.1. Introduction
Now that we have described individual variables (univariate analysis), it is time for us to have a look at the relationship between two variables. This is called bivariate analysis, and will form the subject of Chapters 7 and 8.
In educational research, we often want to look at the relationship between two variables. Do boys do better than girls in reading? Is there a relationship between attendance at school and pupils’ self-concept? These and many other questions necessitate the use of bivariate analyses.
Looking at the relationship between two variables (bivariate analysis) involves a number of different statistical methods, which are related to the different levels of measurement discussed in Chapter 6. If you remember, we said that there were three main levels of measurement: nominal (the numbers are only labels – we can’t order the categories, such as gender), ordinal (we can order the categories, but we can’t say that the difference between the categories is always exactly the same, as with items like ‘I think I’m good at school’), and continuous (can be ordered and distance between categories is always the same, as in height in centimetres). What method we can use will depend on the level of measurement of the two variables we are looking at. If you can’t quite remember what these different levels of measurement are, have a look at Chapter 6.
An important factor to remember when we are looking at the relationship between two variables is that we will want to look at two things: we want to know whether the relationship is statistically significant (low probability of occurring in the sample if there was no relationship in the population) and how large the effect size (strength of the relationship) is. In some cases, the same method will give us information on both these things, but in other cases we are going to need to look at the two separately. Have a look at Chapter 4 if you can’t quite remember what significance and effect sizes are.
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