Have a Look at These Formats for Dissertation!...

There are various formats for writing dissertations. Which method and style you will opt for depends upon your research field as well as your university’s guidelines. The more explicitly you can identify your dissertation pattern, the sooner you can decode the tacit rules about writing. Every research field has a specific template, a method for reviewing literature, a style for dissertation writing, and a method for the dissertation defence. Understand the format for your dissertation writing that is acceptable by your university. Three formats are widely accepted for humanities and social science dissertation: thematic, data analytics, and journal article dissertation. Thematic Dissertation A thematic dissertation is most common in the humanities field. The first chapter of this dissertation is the “Introduction’ and the last chapter is the “Conclusion”. Other chapters focus on various themes related to your subject topic. However, many departments are now moving away from this style of writing a dissertation where published books are an expected part of academic life. Instead, they are accepting dissertation in a format that is reflecting manuscript style which shortens the time to transform a dissertation into a book. Thematic dissertation format: Chapter 1 – Introduction Chapter 2 – Theme 1 Chapter 3 – Theme 2 Chapter 4 – Theme 3 Chapter 5 – Discussion Data Analytic Dissertation Data analytic dissertation is most common in the social science field. The first chapter is the “Introduction” that is followed by “Literature review”, and the third chapter is “Methods” followed by the “Results” section and the last chapter is for discussion and conclusion. Journal Article Dissertation The journal article dissertation is acceptable for both the humanities and social science realms. You should consider this style of dissertation writing if you are required to...

Challenges faced during data analysis...

Data analysis is a systematic technique that assists in the analytical exploration of the study undertaken during research. The objective of data collection, calculation and evaluation are to find out an accurate and apposite result of the problem. However, there are many hitches on the way to reach the result. Below discussed are some of the leading challenges faced in the process – Sample size – Fixating sample size is the first challenge faced during data analysis. For quantitative analysis, sample size can still have a limit of 10-20 in variation, however, for qualitative analysis, there is no such fixed sample size, as it may increase up to a limit where one can get a relevant response. Also, a big sample size is another dare to take on, as it becomes difficult to manage and reach up to the result. Data biasness during sample collection tempts up with the population being reluctant in accepting the sample from outside their circle, this, in turn, dribs a barrier in the study. Reluctance from response – There are times when would be population deny from permitting their sample to participate in the research-based inquiry. This, therefore, is one of the biggest challenges, as you can’t conduct a study, in spite of having the samples. Hawthorne effect challenge – Participants perform and react differently when they feel that they are observed, then their normal behavior. This, however, does not give the real result. Reliability and validity – Data collected should meet the standard of being stable over a period of time, reproductive up to a multiple stages and accurate enough to be applicable statistically. Choosing appropriate methods for calculation – Although brought into action after sample data collection, yet choosing methods for calculation...