Data Analysis (Quantitative and Qualitative)

For data analysis, like in the case of data collection, there are different data analysis techniques at the researcher’s disposal, which we use. For example, for qualitative research, we often categorize data and derive themes, patterns or trends as the primary basis for organizing, interpreting and reporting results. Alternatively, we can analyse it narratively with interesting quotes of the respondents. Content analysis is sometimes used. In quantitative research, we use mathematics and statistical methods and techniques such as correlation analysis, regression analysis, analysis of variance (ANOVA), chi-square test and t-test. It is important to check the data for the relevant assumptions (e.g., normality and independently distributed observations) before we apply particular statistical techniques to analyse the data. The results should be interpreted in relation with the research problem and objectives, and generalized (if applicable). Theories and literature help us to do the interpretation.


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