Data presentation Meaning, Types of Data presentation

 

 

Table of Contents Data presentation Meaning Types of Data presentation 1.     Tables 2.     Charts and Graphs 3.     Diagrams 4.     Maps 5.     Infographics 6.     Dashboards 7.     Statistical Summaries 8.     Narrative Descriptions

 

Data presentation Meaning

Data presentation is the process of organizing and displaying collected data in a clear and understandable manner. Effective data presentation enhances the communication of research findings and facilitates interpretation by the audience. Having analyzed the data that you collected through either quantitative or qualitative method(s), the next task is to present your findings to your readers. The main purpose of using data display techniques is to make the findings easy and clear to understand, and to provide extensive and comprehensive information in a succinct and effective way. There are many ways of presenting information. Some common methods of data presentation include:

9.     Tables

10.  Charts and Graphs

11.  Diagrams

12.  Maps

13.  Infographics

14.  Dashboards

15.  Statistical Summaries

16.  Narrative Descriptions

 

1. Tables: Tables are used to present numerical data in an organized format, making it easy to compare values across different categories or variables. Tables typically include rows and columns, with headings to label the variables and units of measurement.

Tables can be categorized as:

Univariate tables (Frequency Table) – Containing information about 1 variable.

Bivariate tables (Cross tabulation) – Containing information about 2 variables.

Polyvariate or multivariate – Containing information about more than 2 variables.

 

 

2. Charts and Graphs: Charts and graphs are visual representations of data that help convey trends, patterns, and relationships. Common types of charts and graphs include bar charts, line graphs, pie charts, histograms, scatter plots, and box plots. Each type of chart is suitable for different types of data and research objectives. Methods of communicating and displaying analyzed data.

 

Types of graph

 

       I.          The histogram

     II.          Bar chart

   III.          Stacked bar chart

  IV.          100 per cent bar chart

    V.          Frequency polygon

  VI.          Stem and leaf display

VII.          Pie chart

VIII.          Line diagram or trend curve

  IX.          Area chart

    X.          Scatter gram

 

3. Diagrams: Diagrams, such as flowcharts, process diagrams, and conceptual models, are used to illustrate relationships, processes, or systems visually. They are particularly useful for explaining complex concepts or visualizing theoretical frameworks.

 

4. Maps: Maps are used to represent spatial data, such as geographic distributions, locations of study sites, or patterns of variation across regions. Different types of maps, such as choropleth maps, dot maps, and thematic maps, can be used depending on the nature of the spatial data.

 

5. Info graphics: Info graphics combine text, images, and visual elements to present complex information in a concise and engaging format. They are often used to summarize key findings or highlight important trends in research studies.

 

6. Dashboards: Dashboards are interactive visual displays that provide real-time access to data and allow users to explore and analyze information dynamically. They are commonly used in data-driven decision-making and monitoring applications.

 

7. Statistical Summaries: Statistical summaries, such as measures of central tendency (e.g., mean, median, mode) and measures of dispersion (e.g., standard deviation, range), provide numerical summaries of data distributions. These summaries can be presented alongside visual representations to provide context and enhance understanding.

 

8. Narrative Descriptions: Narrative descriptions complement visual presentations by providing context, explanations, and interpretations of the data. Written summaries, captions, and annotations help guide the audience through the data and highlight key insights or implications.

 

The choice of data presentation method depends on factors such as the nature of the data, the research objectives, the target audience, and the preferred communication style. Researchers should select presentation methods that effectively convey the research findings and facilitate understanding and interpretation by the intended audience.