Data analysis involves data collection, organization, Connection of data to show how the variables relate with each other, interpretation of the data and reporting of findings. The data collection method usually defines the type of analysis required. Quantitative and qualitative analysis are the two main types of data analyses. Quantitative involves the analysis of numerical data while qualitative analysis is done on data collected in form of text.
Some of the tools available that support data analysis include statistical packages, spreadsheet, CAQDAS and qualitative data analysis tools.
Data analysis is important because;
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It is also applicable in social sciences and business where it tries to find solutions based on the data collected by finding a relationship between the major variables been analyzed.
Data analysis is the process whereby raw data is examined using statistical tools in order to interpret it is its simplex form. It tries to formulate the data collected from the field by the researcher in a way that it can be used in other disciplines. As a data analyst, you have to be able to use the different statistical tools in order to examine that information for purpose of qualitative research. Get flexible data analysis help online with the convenient experts from economicsheppdesk.com.
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