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.
Advanced Statistical Analysis
In order to run an advanced statistical analysis, you will most likely need access to software such as Matlab, R or Stata. Whichever program you choose to proceed with, make sure that it is properly documented in your research. Additionally, it is extremely important to be able to justify as to why the particular statistical technique was employed. Such a justification lends more weight to your research and makes it more convincing for the readers. Further, using an advanced statistical technique ensures that you are analysing all possible aspects of your data. For example, a difference between basic regression analysis and analysis at an advanced level is that you will need to consider additional tests and deeper explorations of statistical problems with your model. For example, you may explore the type I and type II errors, quality of residuals in the model, consistency of the model with the theoretical framework and alternative methods of estimating coefficients. Also, you need to keep the focus on your research question and objectives as getting deeper into statistical details may distract you from the main aim. Ultimately, the aim of your dissertation is to find answers to the research questions that you defined.
Another important aspect to consider here is that the results and findings section is not all about the numbers. Apart from tables and graphs, it is also important to ensure that the interpretation of your statistical findings is accurate as well as engaging for the users. Such a combination of advanced statistical software along with a convincing textual discussion goes a long way in ensuring that your dissertation is well received. Although the use of such advanced statistical software may provide you with a variety of outputs, you need to make sure to use your own formatting. Inserting raw output from statistical software is an indication of unprofessional writing. Read high-rated academic journals in your field and pay attention to how tables are formatted and the information is presented. Try to keep up with the established traditions found in top journals in terms of presentation of results and their interpretation.
To sum up, it is important to have a firm grip on the topic that you have chosen and the key objectives you pursue. The decision to use specific statistical methods can only be made on the basis of the type of data you have, the subject you study and the degree to what you covered at University. If you are analysing primary data for a management, marketing or business subject, it is more appropriate to go for basic statistical analysis. However, if you write a dissertation in a quantitative field such as economics or finance and use secondary data, you will have to be able to implement advanced statistical methods in order to achieve a first.