{"id":70635,"date":"2019-05-10T05:33:25","date_gmt":"2019-05-10T12:33:25","guid":{"rendered":"https:\/\/www.questionpro.com\/blog\/?p=70635"},"modified":"2024-09-17T04:26:45","modified_gmt":"2024-09-17T11:26:45","slug":"data-analysis-in-research","status":"publish","type":"post","link":"https:\/\/www.questionpro.com\/blog\/data-analysis-in-research\/","title":{"rendered":"Data Analysis in Research: Types & Methods"},"content":{"rendered":"\n\n\n

What is data analysis in research?<\/b><\/a><\/h2>\n\n\n\n

Definition of research in data analysis: According to LeCompte and Schensul, research data analysis is a process used by researchers to reduce data to a story and interpret it to derive insights. The data analysis process helps reduce a large chunk of data into smaller fragments, which makes sense. <\/p>\n\n\n\n

Three essential things occur during the data analysis process \u2014 the first is data organization<\/a>. Summarization and categorization together contribute to becoming the second known method used for data reduction. It helps find patterns and themes in the data for easy identification and linking. The third and last way is data analysis – researchers do it in both top-down and bottom-up fashion.<\/p>\n\n\n\n

On the other hand, Marshall and Rossman describe data analysis<\/span><\/a> as a messy, ambiguous, and time-consuming but creative and fascinating process through which a mass of collected data is brought to order, structure and meaning.<\/p>\n\n\n\n

We can say that \u201cthe data analysis and data interpretation<\/a> is a process representing the application of deductive and inductive logic to the research and data analysis.\u201d<\/span><\/p>\n\n\n\n

Why analyze data in research?<\/b><\/a><\/h3>\n\n\n\n

Researchers rely heavily on data as they have a story to tell or research problems<\/a> to solve. It starts with a question, and data is nothing but an answer to that question. But, what if there is no question to ask? Well! It is possible to explore data even without a problem \u2013 we call it <\/span>\u2018Data Mining\u2019,<\/span><\/i> which often reveals some interesting patterns within the data that are worth exploring.<\/span><\/p>\n\n\n\n

Irrelevant to the type of data researchers explore, their mission and audiences’ vision guide them to find the patterns to shape the story they want to tell. One of the essential things expected from researchers while analyzing data is to stay open and remain unbiased toward unexpected patterns, expressions, and results. Remember, sometimes, data analysis tells the most unforeseen yet exciting stories that were not expected when initiating data analysis. Therefore, rely on the data you have at hand and enjoy the journey of exploratory research. <\/a><\/p>\n\n\n\n

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Types of data in research<\/b><\/a><\/h3>\n\n\n\n

Every kind of data has a rare quality of describing things after assigning a specific value to it. For analysis, you need to organize these values, processed and presented in a given context, to make it useful. Data can be in different forms; here are the primary data types.<\/span><\/p>\n\n\n\n