Charts That Tell the Truth
Choose, build and critique charts that show data honestly and clearly
A taste of a lesson
My bar chart of monthly sales starts at 90,000 so the differences are visible. Is that OK?
For bars, I would avoid it. Readers judge bars by their length, so a bar at 100,000 next to one at 95,000 will look twice as tall when the real difference is about 5 percent. That exaggerates the change. Two honest options: keep bars and start at zero, adding the values as labels, or switch to a line chart, where a zoomed axis is acceptable if clearly labelled. Which matters more for your audience: the size of each month's sales or the change between months?
Written by the teacher as an example. In your lesson the tutor answers your own questions, and like any AI it can be wrong.
What you will be able to do
- Choose the right chart type for comparison, trend, distribution or relationship
- Apply honest baselines and avoid distorting axes
- Recognise misleading techniques such as dual axes and cherry picked windows
- Use titles, labels and accessible colours for clarity
- Critique and redesign charts with a publishing checklist
Lesson plan
- 1 The right chart for the question Match common questions to chart types. Start
- 2 Honest scales Use baselines and axes that represent data truthfully. Start
- 3 How charts mislead Spot common distortions, intentional or not. Start
- 4 Denominators and context Normalise data so comparisons are fair. Start
- 5 Clarity and colour Make the message easy to read for everyone. Start
- 6 Critique and redesign Apply a checklist to improve real charts. Start
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About this tutor
A beginner tutor for anyone who makes charts for reports, dashboards or presentations. You will learn which chart fits which question, why bar charts need a zero baseline while line charts often do not, and how dual axes, 3D effects, cherry picked time windows and missing denominators mislead, sometimes unintentionally. Lessons cover sorting, labelling, colour that works for colour blind readers, showing uncertainty and writing chart titles that state the takeaway. You will critique real style examples and redesign them, and you finish with a short checklist for every chart you publish.
Reviews
4.7
3 ratingsSample
- Thabo M.Sample
The dual axis lesson was eye opening. I would have liked a few more examples from public health charts.
- Noor H.Sample
Clear reasons behind every rule, not just 'never do this'. Colour blind palettes were new to me.
- Isabel Q.Sample
I redesigned our whole monthly dashboard after this. Takeaway titles made our meetings shorter.
About the teacher
Data cleaning, SQL, exploratory analysis and honest charts
9 tutors 427 lessons taught Sample
I teach the part of data science that takes most of the time: getting data into a shape you can trust, querying it, exploring it and showing it honestly. I came to data from operations work, where reports drove real decisions and a wrong join could cost a week. I teach by handing you small, deliberately messy tables and asking...
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