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If you write your work, the process of analysis of data and work with statistics can initially be quite heavy. This is true if you use special data analysis software, such as SPSS or a descriptive approach. However, there are a few guidelines that you can follow to make things easier.
The sheer variety of techniques available for data analysis can be confusing! For example, if you write a thesis about Internet marketing, your approach is very different for someone who writes about biochemistry. As such, it is important to accept an approach that is suitable for your research.
If you work with quantitative data, it is important to ensure that your analytical techniques are compatible with the methods to collect your data. A clear understanding of what you have done so far will ensure that you achieve accurate results.
For example, in performing the statistical analysis, you may need to choose between parametric and non-parametric tests. If your data is scanned from a population with a wide-generated (d. H., Normal) distribution, you almost always want to use a form of non-parametric tests.
If you do not remember or do not remember or not sure how you have selected your sample, you do not necessarily know the best test you can use!
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