Top 10 tips for writing a data analysis dissertation in India

Introduction:

There is a need to collect data for data analysis dissertation. In addition to choosing a strategy, it is important for you to determine the right kind of data analysis process. It should be noted that both words and numbers require careful evaluation. When you are writing a dissertation, you must make sure that your collected data is being analyzed in a competent and most professional way. This is also one of the biggest concerns supporting the thesis for a Ph.D. by data analysis. Data analysis is a time taking and intriguing process. A student should be careful about his or her data analysis dissertation writing. There are top ten tips that can guide you to write a data analysis dissertation in an easy way. These are discussed below:

  1. Relevant data:

You need to make sure that your collected data are relevant and appropriate to the topic. Blindly collected irrelevant data will indicate the writer’s lack of attention and focus that will decrease the quality of your dissertation paper.

  • Analysis of data:

Not just data collection, it is important to analyze the data following the proper procedure. The reader should be persuaded that you did not choose the data analysis method randomly, but that you set them up based on proper thoughts and logic.  

  • Quantitative analysis:

Quantitative data requires scientific and technical research analysis and to a lesser extent sociological analysis and other disciplines. By collecting and analyzing quantitative data, you will be able to present a clear concept to your readers. 

  • Qualitative analysis:

Qualitative data are simple in nature than quantitative data and non-numerical. However, it is wrong to think that qualitative data requires less analysis. You need to analyze qualitative data in a proper way.  the purpose of research work using qualitative data is just not to establish authentic findings, but to expose underlying, transferable knowledge.  

  • Thoroughness:

All data that you want to use to support or refute academic positions should be thoroughly analyzed, especially in relation to potential bias and source of error, showing full engagement and critical outlook in all areas.

  • Presentation:

Presenting large amounts of data in a proper way can be difficult. To overcome this problem, you have to think about an easy way to present all the data in your dissertation. Charts, graphs, diagrams, quotes, and formulas all can give you advantages to present all the data you have collected. Tables are another nice option to conclude, whether it is quantitive or qualitative data. 

  • Discussion:

In the discussion part, you have to show the ability to identify the patterns and themes within the data. Consider different theoretical explanations and balance the benefits and consultations of these different approaches. Discuss the inconsistencies as well as the continuities by evaluating the significance and impact of each.

  • Findings:

The essential points arising after the analysis of the data should be accurately described in the findings part.

  • Appendix:

You may find the data analysis part becomes messed up. For organizing everything, you should make an appendix section and put all the charts, tables, diagrams into this.

  1. Relation with literature:

At the end of your data analysis, it is advisable to start comparing your data with those published by other educators considering points of agreement and differences. Are your searches consistent with expectations, or do they create controversial or marginal positions? Discuss the causes and their associated issues. At this point, it is important to remember exactly what you said in your literature review.

Conclusion:

You need to keep in mind the above ten important tips when you are going to write a data analysis dissertation. Data analysis is a bit complex task and you need to stay focus always.  

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