When writing your thesis, the process of analyzing data and working with statistics can be pretty hard at first. This is true whether you\u2019re using specialized data analysis software, like SPSS, or a more descriptive approach. But there are a few guidelines you can follow to make things simpler.\r\n1. Choose the Best Analytical Method for Your Project\r\nThe sheer variety of techniques available for data analysis can be confusing! If you are writing a thesis\u00a0on internet marketing, for instance, your approach to analysis will be very different to someone writing about biochemistry. As such it is important to adopt an approach appropriate to your research.\r\n2. Double Check Your Methodology\r\nIf you are working with quantitative data, it is important to make sure that your analytical techniques are compatible with the methods used to gather your data. Having a clear understanding of what you have done so far will ensure that you achieve accurate results.\r\n\r\nFor instance, when performing statistical analysis, you may have to choose between parametric and non-parametric testing. If your data is sampled from a population with a broadly Gaussian (i.e., normal) distribution, you will almost always want to use some form of non-parametric testing.\r\n\r\nBut if you can\u2019t remember or aren\u2019t sure how you selected your sample, you won\u2019t necessarily know the best test to use!\r\n3. Familiarize Yourself with Statistical Analysis and Analytical Software\r\nThanks to various clever computer programs, you no longer have to be a math genius to conduct top-grade statistical analysis. Nevertheless, learning the basics will help you make informed choices when designing your research and prevent you from making basic mistakes.\r\n\r\nLikewise, trying out different software packages will allow you to pick the one best suited to your needs on your current project.\r\n4. Present Your Data Clearly and Consistently\r\nThis is possibly one of the most important parts of writing up your results. Even if your data and statistics are perfect, failure to present your analysis clearly will make it difficult for your reader to follow.\r\n\r\nAsk yourself how your analysis would look to someone unfamiliar with your project. If they would be able to understand your analysis, you\u2019re on the right track!\r\n5. Make It Relevant!\r\nFinally, remember that data analysis is about more than just presenting your data. You should also relate your analysis back to your research objectives, discussing its relevance and justifying your interpretations.\r\n\r\nThis will ensure that your work is easy to follow and demonstrate your understanding of the methods used. So no matter what you are writing about, the analysis is a great time to show off how clever you are!