Data presentation is an important stage of research methodology because raw data collected through questionnaires, interviews, observations, experiments, or secondary sources are often difficult to understand in their original form. Data presentation involves organising, summarising, and displaying collected information in a clear and meaningful manner so that researchers and readers can identify important patterns, relationships, differences, and trends. Proper presentation improves the communication of research findings and provides a foundation for statistical analysis and interpretation. The major methods of data presentation include textual, tabular, diagrammatic, and graphical presentation. Textual presentation is one of the simplest methods of presenting data. In this method, the findings are described in words and numbers within a written explanation. It is useful when the amount of data is relatively small and only a few important facts need to be communicated. For example, a researcher studying the employment status of 100 graduates may state that 65 graduates were employed, 20 were pursuing higher education, and 15 were unemployed. Textual presentation allows the researcher to explain the meaning and significance of the figures along with the numerical information. However, when a dataset contains a large number of observations, textual presentation may become lengthy and difficult to compare. Therefore, it is generally used along with tables or graphical methods. Tabular presentation involves arranging data systematically in rows and columns. A statistical table provides a concise summary of a large amount of information and makes comparison easier. A properly constructed table generally contains a table number, title, headings or captions, row headings or stubs, the body of the table, units of measurement where necessary, and a source or note when required. Tables may be classified into simple tables and complex tables. A simple table presents information according to one characteristic, whereas a complex or multiple table presents data according to two or more characteristics. For example, a researcher may present the number of respondents according to gender and educational qualification. Such a table may show males and females in different rows and educational categories in columns. The reader can easily compare the distribution of respondents across categories. Statistical tables may also present frequencies, percentages, averages, ratios, rates, and other statistical measures. Frequency distribution tables are particularly useful because they organise observations into meaningful categories or class intervals. Another important method is diagrammatic presentation. Diagrams provide a visual representation of data and are generally easier to understand than lengthy numerical descriptions. Common forms include bar diagrams, pie diagrams, pictograms, and area diagrams. Bar diagrams are useful for comparing discrete categories. For example, the sales of different products can be represented through separate bars, allowing the researcher to identify which product has the highest or lowest sales. Pie charts represent the components