Data Science and Visualisation
Charts turn data into insight.
About this topic
Data science extracts knowledge from data by collecting, cleaning, analysing and presenting it. Raw data is often messy, with missing values, errors and duplicates, so cleaning takes much of the time. Analysis may use statistics, such as mean, median and correlation, or machine learning to find patterns and make predictions.
Visualisation turns numbers into charts so patterns are easy to see. Bar charts compare categories, line charts show change over time, scatter plots show relationships between two variables, histograms show distributions and maps show location. Good charts have clear titles, labelled axes with units, sensible scales and limited colours. For example, a scatter plot of study hours against test scores may show an upward trend, suggesting a relationship.
Data science supports medicine, sports, weather forecasting and business decisions. A common misconception is that correlation proves causation: ice cream sales and sunburn rise together because both depend on hot weather. Another is that charts cannot mislead, but truncated axes or cherry-picked data can exaggerate results. Always ask where data came from, how large the sample is and what might be missing.
Key ideas
- Clean data first
- Choose the right chart
- Beware misleading axes
Quick check
Use cases: where Data Science and Visualisation helps
- Homework: review the key idea behind Data Science and Visualisation before you start a problem set.
- Exam revision: use the quick check to test whether you can recall Data Science and Visualisation without notes.
- Visual learning: play with the interactive lab to see how Data Science and Visualisation changes when you adjust its inputs.
- Teaching a friend: explain Data Science and Visualisation in your own words, then compare your version with the key ideas.
Computing ideas run phones, search engines, games and the wider internet.
Frequently asked questions
What is Data Science and Visualisation?
Charts turn data into insight.
What will I learn in Data Science and Visualisation?
Clean data first. Choose the right chart. Beware misleading axes.
Is Data Science and Visualisation part of Computer Science?
Yes. It is one of 80 Computer Science topics on LearnViz HighSchoolEdu, with 3 key ideas, a live animation and a quick check.
Does the Data Science and Visualisation lab work on a phone or tablet?
Yes. The animation resizes to fit your screen and supports touch, so you can drag, tap and slide with your finger.
How should I study Data Science and Visualisation?
Read the summary and key ideas first, play with the interactive lab to see the idea in motion, then answer the quick check. If you get a question wrong, go back to the key idea it tests.
Do I need an account, and is my progress saved?
No account is needed. Marking a topic as learned is saved in your own browser, so it stays on that device and is not sent to a server.