You will save yourself a lot of heartache by seeking help on dealing with data before collecting your data. This applies across the entire spectrum of data collection, from qualitative studies (eg, single case studies, textual analysis), through to planned laboratory experimentation with clear, numerical outcomes. Expert help on qualitative data techniques is usually available in social science departments, including sociology, psychology, and education. Most universities employ professional statisticians within their mathematics, economics, agricultural, biological and social science departments. It is their job to advise postgraduate students on how to proceed with their quantitative analyses. Overall, your supervisor should be able to help, or at least point you in the direction of help. Think carefully about the structure of your data, regardless of which method you use. Organise your data in a structured way that reflects the intended method, and the analyses that will follow the data collection phase. Which are your independent variables, which are the dependent? How have you operationalised the aims and concepts of your study? The answers to questions such as these are what you look at to tackle the structure. Once you have collected your data, you may need to seek professional advice, especially if such advice was not sought before you collected your data. If the analysis has a statistical component - which can be as true of textual data as of survey outcomes and laboratory experimentation - organise it so that it is easily accessed by a range of software. Organisation within spreadsheets is often a good way to proceed. They can deal with textual as well as numeric data in a structured way, and be accessed in a straightforward manner from good qualitative and quantitative software analysis packages. The same is true of tables modules in sophisticated word processors; they assist organisational structure which simplifies later analysis. A great deal of invaluable qualitative material ends up unanalysed because it was never transferred to machine readable form. Transferring to machine readable form also drastically reduces error rates on data entry from pencil and paper approaches. There is any amount of good statistical software available nowadays. Elementary analyses can be carried out within spreadsheets and good word processors. There are also software packages to conduct qualitative data analysis, for example NUDIST (Published by Qualitative Solutions and Research Pty Ltd, at Latrobe University; their website is referenced below. Software such as BMDP, SAS, SPSS, NUDIST, etc. and many other exemplars can carry out most of the analyses required in numerical research - which also covers much categorical data collection. SPSS (Statistics Package for the Social Sciences) is one of the best-known statistical software packages; see the main website referenced below. SAS is another very well-known package, it is sold by the SAS Institute and has versions available for mainframes and PCs. The PC version, for Macintosh or Windows, is called JMP; the website link is referenced below. Seek advice on access to analytic software. Most universities maintain licences on popular software and make it available at a reasonable cost; they also usually provide introductory courses that get you started on effectively using the software. After that, courses on individual methods are often available within universities and, in the social sciences, are always available at the summer schools run by the Australian Consortium for Social and Political Research (ACSPRI) in Canberra, and the winter ACSPRI school run in state capitals.

	SPSS Software.
	SAS Institute.
	NUDIST.
	Designing and planning research.
	Looking at the fit between your aims and your research design.
	I've gathered lots of data, finished the experiments, explored the literature. What do I do with it now and how do I put it together?
	Now I see how I should have done it all along. Is it too late to change?
	I am three quarters of the way through but it isn't as fruitful as I thought it would be. How can I rescue my thesis?
	Deciding on your structure.
	Seeing a plot emerge.
	Developing a picture of the thesis as a whole.
	Preparing an outline.
	Is it really necessary to start with a really detailed outline of your thesis?
	Seeking, receiving and handling feedback?
	Strategies for getting the best feedback possible.
	Overcoming reluctance to seek feedback.
	Keeping your research focused.
	ACSPRI
	Consortium Universities Assistance.