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Data visualisations to compare data:

Data visualisation is a powerful method for representing data that would otherwise be difficult to interpret. It enhances clarity by displaying information visually. Key methods include comparing data, showing distributions, illustrating relationships, and revealing compositions. Common tools include charts, line graphs, and scatter plots. Authentic data sources, whether primary or secondary, shape the quality of visualisations. Ensuring data integrity is crucial, as accurate data informs decisions and actions, making validation essential for trustworthy results.

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Data visualisations to compare data:

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  1. Data visualisations to compare data:

  2. Types of data visualisations • Data visualisation is a visual representation of data that would normally be hard to understand • Displaying data in a visual form adds clarity • 4 main ways of using data visualisation: • Comparing data • Showing distributions of data • Showing relationships between data • Showing the composition of data

  3. Types of data visualisations • Data visualisations to compare data: • Tools to compare data: • Charts • Data list • Line chart or histogram • Data visualisations to show distribution of data • Histogram, shows how data has changed over a timeframe, eg. Hrs, days, months, yrs • Line histogram • Scatter charts

  4. Histogram

  5. Data visualisations to show relationships between data: Scatter chart

  6. Data visualisations to show relationships between data: bubble chart

  7. Sources of authentic data • Primary source data, directly acquired from the source • Secondary source data is an interpretation of a primary event or primary source data • Primary source:, obtained through measurement, data-collection forms, eg. Interviews, direct observation, email • Secondary source, gathered from the published work of someone else, eg. Books, etc; online databases, internet.

  8. Data Integrity • Data integrity, the degree to which the data is correct • Data integrity is important because information is used to make decisions and take actions • Validating data ensures high data integrity

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