Communicating Findings and Visualising Data

Question 1

What is data visualisation?

Answer 1

Graphical representation of information or data using visual elements such as maps, graphs and charts.
Visual elements provide an accessible way to see trends, outliers and patterns in data

Question 2

Why is data visualisation important?

Answer 2

1. Enhances understanding - complex data sets can be understanding at glance
2. Facilitates decision-making - clear visual data aids in quicker and better decision-making.
3. Reveals insights - helps to uncover hidden patterns and correlations
4. Engages audience - visual data is more engaging and easier to interpret than raw numbers or text.

Question 3

What is a bar chart?

Answer 3

They display data with rectangular bars representing different categories.
- Ideal for comparing quantities across categories.
- e.g.: comparing sales figures across different months or regions.

Question 4

What is a Histogram?

Answer 4

Similar to bar charts but represent the distribution of numerical data
- Useful for showing frequency distributions
- e.g.: distribution of test scores among students.

Question 5

What is a pie chart?

Answer 5

Circular charts divided into sectors representing proportions of a whole.
- Best for displaying relative percentages of a whole.
- e.g.: market share of different companies

Question 6

What is a scattergram/scatter plot?

Answer 6

Plots data points on a horizontal and vertical axis to show how much one variable is affected by another.
- Excellent for showing correlations between two variables
- e.g.: relationship between hours studied and exam scores.

Question 7

What are area charts?

Answer 7

Similar to line charts but with the area below the line filled in.
- Good for showing cumulative data trends
- e.g.: total sales over time.

Question 8

Strategies for Presenting Findings

Answer 8

1. Tailor presentation - adjust the complexity and depth of data visualisation
2. Match data to visual - use appropriate type of chart or graph to represent data
   **keep it simple to avoid clutter by focusing on key data points.
3. Narrative flow - create a logical flow that guides your audience through the data
4. Highlight insights - emphasise the most significant findings to ensure they stand out.
5. Provide context - labels and legends for graphs and background information to explain significance of data
6. Practice and Refine - rehearse presentation to ensure confidence and clarity, and seek feedback to refine delivery
7. Conclusion