The Art of Dissertation Data Analysis


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Dissertation writing is an art, but, given the high standard that is required to maintain while writing, students find dissertation writing difficult.  From among the many aspects related to dissertation writing â€?data analysis’ is one which forms the very essence of successful dissertation paper. Your doctoral papers cannot dismiss the importance of data analysis.

 

·         Data analysis implies that you present a good interpretation of the data you have gathered and studied. Dissertation writing calls for hard work that has to be undertaken for the extensive hunt for the research materials and references to gather the data. The data is then analyzed carefully and interpreted for the readers.

·         Analyzing is done through a methodology that requires the students to statistically breakdown each and every data gathered and break their complexity. Data analysis is done to prove their thesis and thus it largely depends on the methodology used. The methodology used for data gathering as well as for data analysis is very essential for the success of the dissertation writing. This is where most students find difficulty while writing their dissertation papers.

·         The analysis is largely dependant on the data. If the data is invalid or wrong then the analysis is not worth doing. A single error of your data will cost you, your dissertation. Hence, data gathering has to be done with care and attention. Data should be gathered from sources that are reliable and up to date. When it comes to data gathering or acquiring there are three factors that determine it; namely availability, accessibility and affordability. You can have a good data if you have these three factors. It is lucky to have them all. There may be times when you may not have all three of them. For instance, a government private data may be available to you, because it is circulated through proper channels, but you will never find an access to this data. You might be fortunate to have both availability and accessibility, but if you cannot afford it then there is no help at all. For instance, an extensive study requires lot of money although the data can be easily accessed and is available.

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