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ACTIVITY 1
1. Read about examples of data visualisation techniques below and identify which techniques you have used, along with specific instances where you applied them (https://online.hbs.edu/blog/post/data-visualization-techniques)

Pie Chart- in the presentation to show percentages of the population
Bar Chart - How many people from a population are reprented in the bar
Length of bar indicates how each group measures according to the value. 
They can be too simple for complex data sets. 
Histogram- A level maths- can show frequency density
Gantt Chart- Proccess of time
Heat Map- used during covid to show how many people expereince something by location
Box and Whisker Plot- Becoming a social scientist 20% 
Waterfall Chart
Area Chart
Scatter Plot- in research for essays to show correlation between variables
Pictogram Chart- primary school pictures- accesable way to visualise data
Timeline- in history to see how thigns change over time/prsentation slides
Highlight Table
Bullet Graph
Choropleth Map
Word /
Network Diagram-Economics
Correlation Matric

2. Give examples of bad data visualisation 
Bad labels
Bad clarity
Using wrong graphs/charts
Pie chart with too many categories/variables
Multi colored charts for no reason
Table with no context
Too complex / simple graph for the data set. 

3. There are many online data visualisation platforms available. Pick your favourite data visualisation examples from those platforms and share them with your friends. 
https://informationisbeautiful.net/ 
https://libguides.humboldt.edu/c.php?g=303852&p=2026431
https://public.tableau.com/app/discover 
https://www.voronoiapp.com/

https://informationisbeautiful.net/visualizations/hollywood-2023-hits-flops/

Hint for Q2: https://online.hbs.edu/blog/post/bad-data-visualization


ACTIVITY 2
1. Read this LSE blogpost https://blogs.lse.ac.uk/impactofsocialsciences/2020/05/04/simple-data-visualisations-have-become-key-to-communicating-about-the-covid-19-pandemic-but-we-know-little-about-their-impact/

Discuss with your friends:
1. How do you think data visualisations have shaped public understanding of COVID-19? 
Discuss the ways in which these might have been helpful and (potentially) unhelpful in shaping public opinion and behaviour.
->From simple line charts to more complex chart types, and explores the role they play in shaping public understanding and response to the pandemic.


2. The author of this blog points out that ‘data visualisations can do ideological work’. What do you think they mean by this? What are the risks, in this respect, and how might we guard against them?
->To promote transparency, inclusivity, data accuracy, and ethical standards in the visualization process.

4. What do you think to the author’s suggestion that ‘non standard visualisations’ might be more effective in communicating data about COVID-19?

