Question description Credit card debt is a reality for many in today’s world. Suppose that you had a $5,270.00 balance on a credit card with an annual percentage rate (APR)….
Dissertation and Thesis Data Analysis
Dissertation and Thesis data analysis
Dissertation and Thesis data analysis is the most crucial part of the academic work. It is also the most complicated juncture of the whole research work. Writing a dissertation offers a student a placement for higher education graduation, in addition to open various doors for graduation, publications, and further expansion of the concerned research. The most critical part of the dissertation, which determines the quality of the work conducted is the dissertation and thesis data analysis chapter.
Practically, dissertation and thesis data analysis involves sifting, assimilating, modelling and transforming of data collected by the researcher. It involves transforming the collected data in a form, which would make some logical meanings, for a varied conclusions and recommendations. The data analysis could be conducted in various ways, such as quantitatively or qualitatively. The researcher should choose a suitable model for conducting the analysis, and follow up with diagnostic analysis to test the suitability and accuracy of the specified model.
Dissertation and thesis data analysis procedure should be a consistent one. The data should first be cleaned. Cleaning involves removing irrelevant and wrong data. The data is also coded in a format that it can be understood by the concerned software to be applied. The nest stage is checking the quality of data collected, by reviewing its adequacy and accuracy. These steps are critical before the actual data analysis is conducted. The actual data analysis is then undertaken following the selected analysis model. Our extended services revolves around all these steps. In addition, DataEdy experts are professionals in all data analysis software including Stata, SPSS, E-Views, R-Statistics among others.
The last part of data analysis is its presentation. Analyzed data should be presented in various forms including graphs and tables. The presentation should be easy for the researcher to interpret as well as for the reader to interpret it.