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数据可视化代写 | FIT3179 Data Visualisation Test 4

本次本次澳洲代写是一个数据可视化的Quiz

Content: Test 4 covers all essential materials discussed in the pre-recorded video
lectures and the streamed video lectures from Week 1 to Week 11. Essential materials
are also discussed in the textbook by T. Munzer and other required reading materials
listed on the weekly Moodle pages. Test 4 will not include questions about materials
that are only included in the weekly “Optional Readings”. Test 4 also covers the
following topics introduced during studio hours: HTML, CSS, JavaScript, and Vega-Lite.

You will not be asked to create a Vega-Lite visualisation, but you may be asked to
analyse Vega-Lite code.

Below is a listing of the assessable content discussed during lectures sorted by weeks.

1. Data visualisation definition, data types, marks and channels, channels for
quantitative and qualitative data
Textbook chapters 1.1 to 1.6, 2, 5

2. Table idioms 1
Textbook chapter 7 (pages 146–148, 150–153, 155–157, 168–170), scans from
Kirk 2019 on Moodle.

3. Data-ink ratio, chart junk, how to lie with data vis, storytelling, five design sheet
methodology
Required reading by National Geographic on Moodle

4. Colour, gestalt, visual hierarchy and figure-ground, layout, typography (including
label placement)
Required reading about gestalt principles on Moodle and blog posts by Lisa
Charlotte Rost about use of colour for data visualisation.

5. Idioms for networks and trees
Textbook chapter 9 and scans from Kirk 2019 on Moodle.

6. Table idioms 2 and repeating patterns
Required reading about radar charts and repeating patterns and scans from Kirk
2019 on Moodle.

7. Map projections, map idioms (dot maps, proportional symbol maps, choropleth
maps, area cartograms, flow maps).
Required readings by axismap and scans from Kirk 2019 on Moodle.

8. Scalar field visualisation/terrain visualisation (contour lines, shaded relief, colour
mapping, line integral convolution), web maps

9. Data classification, interactive visualisation
Textbook chapter sections 6.5 and 6.7, required readings by axismaps and Lisa
Charlotte Muth on classification on Moodle.

10. Animation for data visualisation and tools for creating visualisations

11. Immersive data visualisation (mixed reality continuum, virtual reality and
augmented reality)


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