Presentation of Data: Presentation of data refers to the organization of collected data into tables, graphs, and charts. It is easy to draw logical and statistical conclusions from the collected measurements. Data may be presented in text form, tabular form, or visual presentation. Methods of presentation must be determined according to the data format, the method of analysis, and the information to be emphasized. A method of presentation must be chosen after carefully studying the importance of different methods of presentation. However, a table is the most appropriate when all information requires equal attention, and it allows researchers or readers to selectively look at the information of their interest. Graphs allow readers to understand the overall trend in data and understand the comparison results between two groups. The simplicity of presentation is most important in the analysis and interpretation of data.
Text is the method of conveying information as it is used to explain results and trends and provide contextual information. Data are fundamentally presented in paragraphs or sentences. Text can be used to provide interpretation or emphasize certain data. It is more appropriate to use written language than tables or graphs if quantitative information to be conveyed consists of one to three numbers. If more data are to be presented or other information such as that regarding data trends are to be conveyed, a table or a graph would be more appropriate. The text includes a long list of information; the researcher may have difficulties in understanding the information.
A table is a systematic method of presenting statistical data in vertical columns and horizontal rows, according to some classification of the subject. The tablets aim to present the data clearly without cluttering the information. The instructions to authors in a given journal provide information for authors about the number of allowed tables and figures. If not, carefully study the recent papers of a particular journal so that the deletion of tables can be avoided at the time of revision. Tables should not be used for numerical data if the data can be summarized easily in the text or their relationship which can be illustrated clearly in a graph. Tables are very important in writing research papers for presenting the observations in a numerical format because:
- These observations cannot be summarised in the text with a few sentences.
- Relations of numerical data to each other cannot be made more clearly in a graph of illustrations.
- Numerical data contain several variables of a given experimental design or require the presentation of the exact values that are required to make the point.
- Descriptive information or data can be more efficiently presented in a table than in the text.
All parts of a table should be typed double-spaced, including column headings and footnotes.
Good tables are relatively simple, concentrating on a limited number of ideas, effectiveness in conveying ideas, and self-explanatory. Start each table on a separate page. If a table cannot be completed on a single sheet, it can be continued up to a second sheet giving details of the column headings on the next page. The detailed guidelines for the preparation of the table are as follows:
- Tables should be numbered, referred to by the number in the text, and appear in consecutive numerical order within the text. The table number and a concise title should be placed above the body of the table.
- Any descriptive footnotes should be placed at the bottom of the table. Footnotes. used should explain abbreviations, the study conditions, statistical assessments, acknowledge the source of the table, and other details to make the table. understandable by itself. Use the symbols to indicate footnotes as an asterisk (*), dagger (†), double dagger (≠), section mark (§), parallel mark (∥), pound or number sign (#), at the rate (@), a double asterisk (**), etc. or superscript lowercase letters in alphabetical sequence like a, b, c, and so on.
- The title of the table should be specific enough to enable the reader to understand the table. If the title of a column or row headings is long then abbreviate them and explain the same in footnotes.
- Each column heading for numerical data should include the unit of measure for the data. That unit should apply to all data in that column.
- Make sure that all data in a table match with the data presented in the text anywhere else in the paper.
- Tables should be numbered separately in Arabic numerals (Table 1, Table 2, etc.). Never write as data shown in the table above or ‘the following table’.
- Column heading or box heads should be clearly labeled, describing the nature and units of measure of the data listed. If percentages are presented, the percentage symbol (%) should be placed at top of the column, not with the number in the table.
- The cells of columns or rows should not be left blank. If there is no data, the absence should be indicated by an abbreviated notation explained in a footnote, such as ND (not done) or NA (not available or not applicable).
- Do not give more figures after decimal points e.g. 48.38434. Using the law of the whole number round the values e.g. it is 48.38 or 48.39.
- Standard deviation (SD) or Standard Error Mean (SEM) is denoted by ‘ ± ‘ after the mean value in the table.
- Don’t try to use a table to describe any experimental event you can cover in one sentence of the text.
Figures simplify complex information by using images and are useful for summarizing, explaining, or exploring quantitative data. While graphs are effective for presenting large amounts of data, they can be used in place of tables to present small sets of data. A graph format that best presents information must be chosen so that researcher can easily understand the information. The difference between graphs and diagrams is given in Table.
|1. Graph paper is used for the preparation of graphs||1. Plain paper is used for drawing or construction of diagrams.|
|2. It represents the mathematical relationship between two variables.||2. It does not show any relationship in variables.|
|3. Graphs are commonly used to represent frequency distributions.||3. Diagraphs are not used for frequency distributions.|
|4. Graphs are commonly used by the researcher for the analysis of data.||4. Diagrams are not useful for the analysis of data.|
|5. For example: Line graph, frequency.||5. For example: Pie diagram, bar diagram, curves.|
Make sure you also check our other amazing Article on : Types of Research Reports