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Analysis &
Interpretation

Data Analysis and Interpretation

Data analysis is the process of providing structure, order and meaningful insight to the collected data that ensures your findings are accurate, applicable and reliable. On the other hand, interpretation of data is the process of explaining the discovered patterns. These allow you to identify the patterns, draw conclusion, link your research findings to existing literature and adding the deep value to your research work.

What is Data Analysis?

Data analysis is a logical or statistical technique to explain, compare and summarize data. The feature of data analysis is to detect useful information, helps decision making and suggest conclusion. It also includes organizing raw data and using strong methods to acquire trends and patterns.

What is Data Interpretation?

Data interpretation includes describing the result in a meaningful way and drawing connection between both findings and your research questions. It also explains the contextualizing in broader field of study. It answers the “why” supporting your findings and connects the dots between empirical data and theory.

Significant of Data Analysis and interpretation

Data analysis and interpretation is essential for the reason that they allow researchers to,

  •    They directly answer research questions and hypotheses by formulating raw data into clear answers.
  •    Data analysis and interpretation helps researchers to draft a conclusion that are leading credibility to the study.
  •    They support identify important patterns that lead to new insights, further research and theories.
  •    Clear analysis and interpretation support to prevent bias by aiming to ensure that the conclusions are depends on actual data.

Data Analysis Methods

The methods of analysis based on the types of gathered data and the research design. Here are some common methods used in different types of research,

  •    1. Quantitative Data Analysis: This analysis involves statistic methods such as descriptive statistics, inferential statistics and software tools. Descriptive statistics can summaries the basic features of data such as medians, media and standard deviation. Inferential statistics helps to make inferences in population based on the sample using hypotheses testing or regression analysis. Use statistical software like EXCEL, SPSS, R, SAS are used for quantitative analysis.
  •    2. Qualitative Data Analysis: Analyzing the frequency of specific words or themes in text or images. It identifying and analyzing themes or patterns within qualitative data. Using tools can helps you to organize and analyze qualitative data.
  •    3. Mixed-Methods Analysis: This analysis can combine both qualitative and quantitative methods to provide extensive understanding of research problem.

Virtual Data Interpretation

  •    The primary goal of interpretation is to link findings to research questions. Ensure that your interpretation is directly related to these questions and objectives to achieve.
  •    Interpret your research findings into contextualize result of the existing literature. Compare your result to other researchers have similar studies. This strengthens the relevance and importance of your work.
  •    Consider the limitation in your data, interpretation and analysis. This includes bias, sample size or external factors that influenced the result. Limitation improves the validity and reliability of your research.
  •    Avoid making simplifying interpreting data and conclusion to get prejudgment content. Ensure that your interpretation is based in the sound evidence.

Data Analysis & Interpretation Assistance

You need to interpret the provided textual or narrative data, such as thematic analysis, content analysis, or any grounded theory that you have provided in your thesis. It’s very important to provide examples of coding schemes, themes, or categories that you have identified during qualitative data analysis in your thesis, and also it’s very important to illustrate in a very accurate manner as well. We have experts for data interpretation and data analysis; they will thoroughly guide you with your thesis and also make you understand every interpretation techniques very easily by their unique guidance. So, hereafter you need not to worry about any data analysis or data interpretation issues in your thesis, we are always there to help you promptly.