Data organization entails the techniques of classifying data and thus enabling them to be more useful. Organizing data allows the statistician to easily trace the data efficiently and use them accordingly when in need of application on a real-time basis. It is essential for the establishment of a data organization for easy access to the data. Data organization depends on its nature. Qualitative data is organized through contingency tables and summary tables while quantitative data is organized through frequent distributions and ordered set. Qualitative data is organized through reviewing the whole set of data to identify the respective patterns, create a code table for code consistency and enhance easy accessibility when needed, divide the data into groups then organize the survey data by questions and subtopics. Finally code transcribing is essential to strengthen evidence of the data(Bhat & Dhebri, 2019). Quantitative data is organized by analyzing the structures of data, designing the databases, decision making regarding categorization and normalization, Pareto chart and by bar charts.

Data has to be visualized after being organized. The purpose of visualizing data is to clarify the analysis and frequency distributions of the data collected and organized. Qualitative data is visualized through pie charts. Qualitative data is visualized through a continual analysis process. Visualization of data is done through by identifying the data to be presented, arrange the data into tables and differentiate the tables accordingly. Quantitative data is visualized through making comparisons of the data collected and designing the model to visualize the data. This makes the quantitative data to be analyzed clearly for easy analysis and comparison in statistical methods.

References

Bhat, M., & Dhebri, P. (2019). U.S. Patent Application No. 15/987,881.

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