There are a large number of techniques for analyzing data. Which techniques you have to use depends on what you want to do and also on the type of data you are using. Descriptive statistics are used to show the central tendency (e.g. mean) and dispersion (e.g. standard deviation) of a single variable, or the strength and direction of the relationship between two or more variables. Inferential statistics are concerned with making generalised conclusions on the basis of your data – in other words, when you are trying to infer whether patterns observed in the data also exist in some wider population. Inferential statistics involve conducting statistical ‘tests of significance’. For both types of analysis, the choice of technique is shaped by the type of variables you are using – that is, the level of measurement of your variables.
Textbooks and online resources should be consulted to help you decide on the appropriate techniques to use. To start with, you can also use this online tool for selecting statistics. This tool asks you a series of questions and then tells you which techniques are appropriate for your analysis. Before using this tool, you should decide:
- how many variables you want to analyze together
- the level of measurement of these variables
- whether you are interested in describing a single variable, measuring the strength of a relationship or performing a test of significance
More detailed information about statistical techniques can be found in the textbooks listed below, or on websites such as statsoft.com
To analyze data, you will need a statistical software package such as SPSS (you can find out how to get it here). The ‘Handbook of Statistical Analysis Using SPSS’ provides a very clear and complete text on statistics and the use of SPSS. Other useful statistical software packages include STATA and Minitab.
You may need to refresh your knowledge on algebra in order to understand some of the concepts and techniques involved in statistical analysis. The SOS website provides a good introduction.
In order select the correct method of analysis for (1) comparing groups or (2) identifying relationships, you can have a look here.
- Babbie, Earl (2004). The Practice of Social Research (12th edition). Belmont: Wadsworth/Thomson. Chapter 16.
- De Vaus, David (2001). Research Design in Social Research. London: Sage. Chapters 6, 9, 12.
- De Veaux, Richard, Paul Velleman and David Bock (2008). Stats: Data and Models (2nd edition). London: Pearson/Addison Wesley.
- Agresti, Alan and Barbara Finlay (1997) Statistical Methods for the Social Sciences. Upper Saddle River, Pearson.
- Agresti, Alan (2007) An Introduction to Categorical Data Analysis. New York, Wiley
- Woolridge, Jeffrey M. (2009) Introductory Econometrics: A Modern Approach (4th edn). Mason: South-Western.
- Carroll, J. Douglas and Paul E. Green (1997). Mathematical Tools for Applied Multivariate Analysis (2nd edition). San Diego: Academic Press.
- Achen, Christopher (1982) Interpreting and using regression. London, Sage
- Andersen, Robert (2008) Modern Methods for robust regression. London, Sage
- Fox, John (2008) Applied Regression Analysis and Generalized Linear Models. London, Sage
- Gelman, Andrew and Jennifer Hill (2007) Data Analysis using Regression and Multilevel/ Hierarchical Models. Cambridge, Cambridge University Press
- Hardy, Melissa A. and Alan Bryman (eds) (2004). Handbook of Data Analysis. London, Sage.