#14 Data Visualisation in Charts, Graphs & Tables

s2s · April 21, 2023
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Objective: By the end of this course, you will understand the importance and application of data visualization in a variety of contexts. You will have the skills to create effective charts, graphs, and tables to represent complex data clearly and accurately.


Lesson Title:
Data Visualization in Charts, Graphs & Tables

Course Module: STUDY READY

Target Audience: International students entering the tertiary education system.

Lesson Objective: Students will understand the foundational principles of data visualization and learn to effectively apply these principles to create clear, accurate, and visually appealing charts, graphs, and tables. This skill will enhance their ability to present complex data in various academic and professional contexts.


Introduction: Welcome, students! Today, we dive into the essential skills of data visualization. As you begin your academic and professional journeys, the ability to communicate quantitative information will be invaluable. Data visualization is not just about making striking visuals; it’s about enhancing understanding and facilitating better decision-making through the effective presentation of data.

Understanding Data and Its Importance: Before creating visuals, we must first understand our data. Data comes in various forms, and understanding the type of data is crucial:

  • Quantitative Data: This includes measurable quantities and numbers. Examples are height, weight, and age.
  • Qualitative Data: This involves non-numerical information that describes categories or characteristics, such as types of animals or genres of books.
  • Time-Series Data: Data points indexed in time order. This is particularly important for trend analysis over time.

Principles of Effective Data Visualization: To effectively visualize data, there are several principles you should follow:

  1. Clarity: The visualization should make the information clearer, not more complicated. Avoid unnecessary decorations that do not add informative value.
  2. Accuracy: Visualizations must represent the underlying data truthfully without distorting the facts. For example, ensure that axes are appropriately scaled to not mislead the viewer.
  3. Relevance: Every element in the visualization should contribute towards understanding the main message or goal of the data presentation.
  4. Consistency: Use consistent elements in terms of colours, fonts, and layout, which helps reinforce understanding rather than confusion.
  5. Accessibility: Ensure that your visualizations can be understood by people with disabilities, such as those with colour blindness.

Exploring Types of Visualizations:

  • Charts: We’ll explore how to use different types of charts effectively. For example, pie charts are best for showing parts of a whole, whereas bar charts are better suited for comparing quantities across different groups.
  • Graphs: We will cover when to use various types of graphs, including line graphs for displaying data changes over time and scatter plots for showing relationships between two variables.
  • Tables: While less graphical, tables are crucial for presenting raw data with exact figures. They are especially useful when specific numerical values need to be communicated.

Creating Effective Visualizations: To put theory into practice, we’ll work through examples:

  • Example 1: Using a bar chart to visualise survey data on student satisfaction ratings across different courses.
  • Example 2: Using a line graph to display historical changes in the population of a specific region.
  • Example 3: Creating a table to compare economic data from multiple countries, focusing on GDP and population.

Common Pitfalls in Data Visualization:

  • Overcomplication: Trying to display too much information in a single visual which can lead to confusion.
  • Inappropriate Use of Visualization Types: A pie chart can show changes over time, which is inherently misleading.
  • Neglecting the Audience: Failing to consider the audience’s background knowledge and what they can understand from the visualization.

Conclusion: Effective data visualization is a potent tool in your academic toolkit. By mastering these techniques, you’ll enhance your ability to communicate insights derived from data, paving the way for informed discussions and decisions based on clear, compelling presentations.

Quiz: To reinforce today’s learning, we’ll conclude with a quiz. This will assess your ability to select appropriate visualization tools for different types of data and to recognize effective versus ineffective visual presentations.

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