In a research process, data analysis is considered as a crucial aspect as it helps in structuring the findings and provides meaningful insights to the critical decisions. In this step, cleaned data is put into analysis tools for identifying patterns, formulating results so as to make meaningful inferences and conclusions.
Conducting data analysis is not every scholar’s cup of tea. One should know the types of data analysis, which approach one must use, how to perform it and which statistical tool one should use for each type. If done in an inaccurate manner, data analysis can ruin your study in one-shot. Below are a few tips that have the potential to help you with data analysis process and save your study.
- Define your research question – Design the question such that they are measurable, concise, clear and can qualify potential solution.
- Set measurement priorities – This step can be broken into (a) what to measure (b) how to measure it. (a) Here you will have to determine what type of data you will require to answer your research questions. Once the data surrounding the main question has been obtained, you have to ask yourself a few secondary questions. All the data obtained and the secondary questions can then be converted into useful information. It is vital to choose the apt data, the reason is that the data collected will determine how it gets analyzed in the later stage. (b) Your research dictates the research methodologies you use to measure the variables. For example, if you have collected quantitative data, you will be measuring variables and verifying existing theories/ hypothesis/ questioning them. Data is often used to create new hypotheses, that is based on the results of the data collected.
- Gathering of data – The next phase gathering of data. Before gathering the data, check if there is any data available relevant to your research questions. Decide which method you will be using to gather data; Questionnaire method, survey method etc. It is always advisable to collect data in a simple and organised form. Once you have collected the data, screen the information for its accuracy.
- Data scrubbing – Data scrubbing, also known as data cleansing, is the process where incorrect data is removed. Some of the data you have gathered may be duplicated, may be incomplete, or redundant. Through this you can eliminate all such “dirty data”.
- Data analysis – Now that the data is collected, the next step is to analyse it. You can use various methods and tools for this purpose. Approaches:Descriptive statistics, inferential statistics, exploratory data analysis and many more. Tools: SPSS, STATA, SAS etc.
- Data interpretation – Once the data has been analyzed, it can easily be interpreted. Does it help you with any of your objections? Are the results limiting or inconclusive? etc. If all your research questions are dealt with the data gathered accurately, then your research can be considered as complete.
The data analysis process is very intensive. Different researchers prefer different approaches. Some may prefer to use the software as the main way of analyzing the data, while others may use the software only to organize and manage the information.