Data Analysis

• Data Analysis

  • A process of inspecting, cleaning, transforming, and modelling data with the goal of underlining essential information, suggesting conclusions, and supporting decision making. The process which follow data collection
• Data Cleaning: Collected data pass through the process of cleaning to remove ambiguous elements. Content analysis is also applied to capture information from the open-ended questions which are subject to quantification in a quantitative research.
• Data Coding: Refers to the process of assigning numerals or other symbols to answers so that responses can be put into a limited number of categories (Connelly, 2000, in Arcinas 2016).
• Data Presentation: Tables and figures are used to summarize the coded data. When using computer programs such as MS Excel or Advanced statistical packages like SPSS or Minitab Software, functions are provided within the program for summarizing data into either tables or figures.
• Data Interpretation and Discussion: It involves the provision of comments on the results obtained from the investigation. It is done based on the key findings of the study. Interpretation requires deep understanding of literature and issues under investigation. The interpretation of the data must be within the framework of what the data analyzed, suggestsm and not an exaggeration. Statements that are not justified by the data do undermine the credibility of what is being presented. As such, interpretation should be done in context and supported by literature.