What is Data Analysis?
Data Analysis is defined as a process used by researchers to reduce, transform, and model data to discover useful insights by reducing a large data into smaller part. During the process of data analysis, three important things happen: (1) Data Organization, (2) Data Reduction & (3) Data Analysis. In a research paper, the data analysis section is written right after the approaches and tests used. Through this section, it is demonstrated how you organized your data, what statistical methods were applied, and how you assessed the acquired outcome.
Here are the some of the helpful tips to consider when writing your paper:
- Never analyze the results in the data analysis section of your research.
- Determine whether the research method you used is either quantitative or qualitative.
- Present your key research questions and the analysis approaches that were used to answer them.
- State which tools or software has been used in collecting and analyzing your data.
- Record a complete list of the data sources, which include digital archives and online reports of various institutions.
- Make clear explanation of how the data were summarized and what standards of variability you have utilized.
- Keep in mind to discuss about the data transformations, including data normalizing.
- Include the full name of statistical tests used.
- When analyzing the raw data and the results, explain the graphical techniques used.
On the other hand, you can look for expert advice from people who have done successful data analysis or you can start to hire a reliable Data Analysis Services.
Types of Data in Research
Every type of data possesses an odd quality of explaining things once assigning a particular value to it is carried out. For data analysis, it is required to organize these values, and process it in a given context to make it useful. Below are the primary types of data:
- Qualitative Data: It is considered to be semi-structured or unstructured in nature, which can be generated through audio and video recordings, interview transcripts and focus groups, texts and documents, images and symbols, as well as observations and notes. It is typically used to answer the question “why” and can be used for developing hypotheses and preliminary understandings, as well as for interpretations and theorizations.
- Quantitative Data: In contrast to qualitative data, it is considered to be structured in nature, which can be generated through experiments, tests, market reports, surveys and metrics. It is ideally used to answer the question “how much or how many”.
- Categorical Data: It is usually divided into groups such as age group, sex, race and educational level, for example. It can be generate through the use of data tables. This type of data can take on numerical values, for example, using numbers “1” to indicate male category and “2” to indicate female category. However, those designated numbers do not have mathematical meaning.
The importance of data analysis in research has been very evident as researchers fully depend on data as they have to formulate or develop a story in order to solve a problem. It begins on asking a specific question and data is used as a tool to answer that question. Researchers are expected to analyze data in an open and unbiased approach towards unexpected patterns, expressions and outcomes.
Data analysis is not an easy task to do, most especially if you do not have sufficient knowledge or experience in carrying out such activities. Therefore, you can freely seek for assistance from experienced people or even hire the best Data Analysis Services in the UAE.