Top 7 Tips For Writing A Dissertation Data Analysis

Students quite often struggle to write a dissertation and ask about “Top 7 Tips For Writing A Dissertation Data Analysis”. Here is a breakdown for our students so that they can write productively. If you are interested in writing a perfect dissertation read the article below:

Understand Data Analysis in Dissertation

Dissertation Data Analysis is the process of understanding, collecting, and compiling a large amount of your research data. It is important to identify common patterns and examine facts and figures to look for the reasoning behind the results.

It is just not enough to collect and compile the data in the form of facts and figures. You need to do the data analysis to use it properly in the dissertation. The analysis provides scientific support to the dissertation and its conclusion.

Following are the Top 7 Tips For Writing A Dissertation Data Analysis. Make your life easy by focusing on these tips:

1. Analysis Must Be Relevant To The Collected Data

Keep a check on your collected data whether it is relevant or not because sometimes under the pressure of doing the dissertation, the student gets confused. But it is important to focus on what is important and what is not and if it is relevant to the topic or not. 

You must carefully analyze for suitable results and conclusions. Do not add information that is not needed just to increase the length of the dissertation. Make sure to fit your objectives and be aware of the research so that it may help you in the analysis. 

Stay relevant and focused to generate appropriate results from the research data. The dissertation’s main purpose is to check your research skill, and how you search, analyze, summarize and conclude the topic you have given. 

NOTE:  Focus on the relevancy of the research data so you can analyze and get results staying in that specific topic.

2. Data Analysis

It is crucial to use effective analysis methods to fulfil the objectives of the research. Make sure you justify your data collection methods completely. The reader should get the idea that you choose your method smartly. You are here after prolonged research don’t forget to choose the data analysis wisely.

Data analysis implicates two methods

• Qualitative Data Analysis
• Quantitative Data Analysis

Qualitative data analysis includes research through the following:

• Experiments, 
• Focus groups
• Interviews. 

This method helps you to gain the objectives by recognizing and researching everyday patterns acquired from responses. 

On the contrary, quantitative analysis directs the analysis that involves the interpretation of facts and figures. Quantitative analysis helios you build reasoning behind the start of prior findings. 

The overall purpose of data analysis is to notice and observe trends and patterns in data. It helps in offering a solid base for evaluative conclusions to complete the dissertation. 

3. Qualitative Data Analysis

Qualitative data is data that does not include numbers. This analysis is a little time taking as it requires analysis of collected data through focus groups, interviews, or experimentation. You need to understand that qualitative data analysis not only generates outcomes but in-depth knowledge that is transferable. 

It is a challenging task to present qualitative data analysis in a dissertation. The qualitative analysis is longer and is in more detailed responses. It is difficult to judge which information to include and which to exclude so figure it out wisely.

Methods For Qualitative Data Analysis

The quantitative data analysis is performed by the following methods:

•  Inductive Method

In the inductive method, the research is not analyzed on the basis of predefined rules. The students who are not known about the research phenomenon usually adopt this method. This method takes quite a long time to do the analysis. It is very time-consuming.

•  Deductive Method

The Deductive method involves analyzing qualitative data that already defines the argument that a researcher does. They get a quite amount of results through the responses they receive from the questionnaires. It is a very suitable method and produces effective results.

4. Quantitative Data Analysis

Basically, quantitative data consists of facts and figures conspired from scientific research that involves large-scale statistical analysis. For concluding the collection of data and analysis it is important to state factual information. Statistical analysis is an important aspect of the dissertation to give it a complete look.

Methods For Quantitative Data Analysis

Methods for Quantitative data analysis are as follows:

• Cross-Tabulation: 

A tabula way is a method to draw readings among the data sets in the dissertation’s research.  

• Gap Analysis:

It uses a side-by-side matrix to show captured quantitative data and the difference between the actual and regular expected performance. 

• Conjoint Analysis: 

It is a method that can help you analyze and collect advanced calculations. These calculations provide a complete vision of marked parameters and fixed decisions.

• Trend Analysis: 

A statistical analysis approach so you can look at the trend of quantitative data accumulated over a considerable time.

• TURF Analysis:

This method estimates the complete market reach of a product or service.

• Text Analysis: 

In this method, creative tools set out open-ended data so you can easily understand data. 

5. Data Presentation Tools

As we all know dissertation is a lengthy paper that needs to be presentable to easily understand it. For this purpose, you need to be creative enough to leave an organized impression by using multiple choices. Some students find it difficult to present such lengthy content in an organized manner. So, search for the best ways to make your dissertation look creative.

You can use tables, diagrams, charts, and graphs to sort your information in a more effective way. This is a way to attract readers. Tables and diagrams show the very presentable look of the dissertation.

You can display both the qualitative and quantitative data in tables or diagrams to make a major difference. For example, if factual data are written in a  paragraph versus data written in a chart/table, the chart/table will gain more attention than the paragraph.

6. Include Appendix 

After completing the dissertation, add a page of the appendix so that it can help the reader to understand some terms that they do not know. An appendix provides supplementary material that is not important yet it helps in understanding some of the difficult terms.

It is a part of the structure of the dissertation. Also, it depends on the university’s guidelines. If it is asked then surely don’t miss adding this section. 

Luckily you are almost done with the dissertation. It’s essential to advise the students not to submit the dissertation right after it is done. Make sure you proofread it twice to avoid mistakes and blunders.

7. The thoroughness of Data

You have to make sure that your data is providing complete sense. It is not the reader’s duty to understand everything you have written. Instead, it is your duty to write and analyze the data in such a way it provides proper sense, i.e; complete paragraphs, sentences, and research.

Comprehensively explain the ideas and critically examine each viewpoint taking care of the points where mistakes can arise.

Some More Tips That Can Help You:

• Discussing Data

Discussion should involve the complete elaboration of your dissertation. Don’t miss out on classifying the structure, theme, and terms presented in your dissertation. Discuss the reliability of your dissertation and take academic understandings into account. Use relevant quotes and be creative.

Explain what are the pros and cons of the data and which methods you use. Make sure to develop an understanding dissertation so readers don’t find it difficult to interpret the dissertation. All research questions should be answered in your dissertation.

• Findings and Results

Your finding should be very precise and to the point. Make sure it has no suspense and the reader can easily understand the result of the research. The collected data should clearly state the purpose of the research, so it must be logical and scientifically backed.

Give the readers complete understandable answers. Results should be concise and perfectly conveyed. 

Don’t Forget To Follow These Rules

• Check data analysis dissertation examples to get an idea.
• Keep it authentic and precise. This is a golden rule because it is important to make the dissertation readable. As the dissertation is a lengthy paper, applying perfect structure can help the reader to understand it easily.
• Conduct analysis in dissertation properly.
• Be specific and relevant. Start with the title page and then the introduction as instructed by the supervisor. 
• Focus on the key findings and appropriate statistical analyses.
• Your content of the dissertation should answer all of the research questions.
• Don’t forget to use the past tense in describing results.
• Do not duplicate the same information in more than one structure.
• Select the best way to convey the message.
• Don’t copy and write on your own. Plagiarism is illegal.
• Use efficient and effective methods to analyze data.
• Your dissertation should be complete.

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