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# What Type of Statistical Analysis Should You Include in the Results and Findings Chapter of Your Dissertation

The results and findings chapter is one of the most important parts of your dissertation. This is because you demonstrate your unique research abilities in this chapter. That’s why it often accounts to around 40% of the total mark. Typically, this section provides an output of calculations, interpretation of attained results and discussion of these results in light of theories and previous findings. Oftentimes, the discussion is further separated into a new chapter. Since calculations and interpretation of findings are essential elements in your analysis chapter, it is important to discuss what type of statistical or econometric analysis you can include to maximise your chances of getting a first.

## Basic Statistical Analysis

The type of statistical analysis that you choose for the results and findings chapter depends on the extent to which you wish to analyse the data and summarise your findings. As the first step, it is important to present the variables. This is often done through summary descriptive statistics. All variables pertinent to your research need to be clearly defined. Thereafter, on the basis of these, you need to assess whether a basic statistical analysis will suffice or there is a need to dig deeper and provide a more in-depth analysis. For instance, if you do not major in quantitative subjects but write a dissertation in social sciences, basic statistical analysis will be sufficient. What should a basic statistical analysis include?

As said before, descriptive statistics will be an essential part. Such an analysis would be based on metrics such as the mean, the median, standard deviation, and variance. Then, you can enhance the statistical analysis with visual information by showing the distribution of variables in the form of graphs and charts. Such an analysis can be easily done in Microsoft Excel but oftentimes research in social sciences includes analysis conducted in SPSS. This software is useful for running ordinary regressions and correlations. Estimating cross-tabulations and comparing the means of variables using ANOVA and t-statistics are also considered basic elements of statistical analysis that most students are expected to be aware of. However, if you major in a quantitative subject and pursue research in economics or finance, you may need to use more advanced statistical analysis.