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Dissertation Methodology & Analysis

Please find below details of our specialist service for students looking to order a customised dissertation methodology and data analysis, either as part of a full dissertation order or as a standalone piece.

The Importance of Your Methodology & Analysis

Most students completing a Masters dissertation will need to include a methodology and analysis section.

  1. Your Methodology - Your methodology is the critical section of your work where you explain the procedures, methods and techniques that you used for the collection of your primary data. It is also here that you analyse the reliability and breadth of your data collection techniques and thus build the platform from which to later judge the overall soundness of the conclusions you reach at the end of your dissertation.

    Nonetheless, many students find their methodology to be the most difficult part of their dissertation. This is mostly due to the fact that most students have not completed a full-length methodology or analysis before and therefore are not familiar with the particular theoretical, structural, formatting and referencing requirements for these types of work. Moreover, many students fail to give a comprehensive or clear enough description of the actual methods they employed in their primary data collection, but rather give a much too vague and generalised account of the procedure.

  2. Your Data Analysis - Correct statistical analysis of data is one of the most difficult aspects of your dissertation. No matter whether you are using a specific data analysis program such as SPSS or Linux, or whether you take a purely descriptive and non-technical approach, the analysis of primary data can be an intimidating and arduous task.

    If you plan to use a quantitative statistical analysis as part of your research project, every aspect of your experimental design must be checked against the statistical test you plan to apply. Students, particularly at Masters level, often come across serious problems when it comes to applying a valid and informative statistical test, because their method did not meet the requirements of the test. There are various fundamental principles to experimental design including replication, randomisation and blocking techniques. Forgetting to include such principles in a methodology will result in an unnecessary, insignificant statistical result.

    Statistics can be extremely simple or extremely complex. Often the problem lies with a poor understanding of statistics at the very basic level, leading to complete lack of understanding at higher levels.

    One of the most common mistakes students make is when they come to choose the type of statistical analysis to perform. For example, one must decide whether the data is suitable for parametric or non-parametric testing.

    Important features of parametric testing include:

    • ANOVAs
    • Regressions
    • Taking more than one explanatory variable into account.
    • Combining continuous and categorical variables.
    • Analysing interactions between explanatory variables.
    • Checking that the statistical model is valid.
    • Model selection and experimental design.

    Non-parametric tests include:

    • Chi-squared contingency tests.
    • Mann-Whitney test.
    • Kruskal-Wallis test.
    • Friedman's test.

An Oxbridge Essays Methodology & Analysis

If you order a customised methodology and analysis from us, it will be written by an expert academic in your subject with considerable personal experience of preparing such works.

Your methodology will give a powerful and comprehensive description of the methods and techniques you employed to gather your primary research and will therefore add major credibility to the conclusions you reach at the end of your dissertation.

Your data will be professionally analysed and represented using the most suitable programs for your particular results, and will therefore give you a major advantage over other students whose data analysis will not be anywhere near as professional as yours.