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In Search of an Excellent Data Analysis Section Example for Your Research Paper

Data analysis in research paper confuses a lot of students when it comes to qualitative studies. This is because it demands a lot of time and critical thinking. Computers play an important role in this section of a research paper but it is crucial to know how to present data. This paper seeks to clarify the different approaches used to analyze data.

Two essential approaches

  • Deductive analysis
    This is the method in which a pre-determined structure is employed. Basically, the writer develops their unique framework of analysis and theories based on collected data. The same approach applies when analyzing say interviews and it is very helpful when the researcher can predict the answers of the interviewees.
    In a research paper data analysis example, the researcher wants to establish why patients have been complaining about a particular doctor. If a questionnaire is used, some obvious options would be traumatic experiences after treatment, doctor’s misconduct, and poor communication. The analysis of data would scrutinize each option to find out for instance how many victims were assaulted by a doctor and if there was co-occurrence of issues. Nevertheless, while it seems so easy, the approach is less flexible and could be biased due to the predetermined framework. This limits the development of theories and themes.
  • Inductive analysis
    In this approach, there are no predetermined structures or theories. The real data is used to induce the analysis framework. For this matter, the approach is more comprehensive and laborious. It applies best in little-known or unknown areas of study.

3 useful tips for data analysis

  1. Begin with descriptive statistics
    Before tackling the complicated stuff, it is better off to start with the basics. Descriptive data offers critical perspective of the complex procedure, making interpretations easier.
  2. Data trimming
    Streamlined data is easier to focus on. Unnecessary variables should be eliminated. However, the original database should be saved separately for reference. The master copy should be set aside when doing the analysis.
  3. Basing assumptions on theory
    Hypotheses should be derived from theory rather than the collected data. It would be a waste of time to try to explain a concept which literature doesn’t support or is founded on errors. This is why it is important that the assumptions be made clear before analysis.

Even if there is no silver bullet to analyzing data in research work, students can apply the above hacks to avoid common mistakes and make their project smoother.