Almyra Zahra 103148055 - COS30045 4.1 Design Studio
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Swinburne University of Technology *
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30045
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Apr 3, 2024
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Almyra Zahra 103148055 1
School of Science, Computing and Engineering Technologies COS30045 LAB 4.1 Design Studio
Overview
In this lab you will be given a sample data set and asked to identify the different data and attribute types. You will
also think about some questions about this data set that might be answered by a visualisation.
ardd_fatalities_Jan2020_0.xlsx (download from Canvas)
Download and review this data set before attempting this exercise.
1 Interpreting the data set
Complete the LAB 4.1 Quiz.
2 Visualisation Design
Think of three questions you would like to answer with that require a data visualisation. For each data question you will need to consider the following:
Which data attributes (columns) do you need to answer this question?
Do you need to transform any of the data?
Does the data type change when you transform the data? If so how.
Make a sketch of how you think your visualisation might look and add to this document.
Question 1 - What is the distribution of fatalities by age group?
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Data Attributes Needed: Age group, Crash ID.
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Data Transformation: Grouping the data by age group.
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Potential Data Type Change: No change in data type because there are predefined age groups (categorical), otherwise may need to aggregate data if using raw age values.
Almyra Zahra 103148055
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Question 2 - How does the distribution of fatalities vary within different times of the day?
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Data Attributes Needed: Time, Crash ID.
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Data Transformation: The data needs to be grouped or categorised based on different time intervals within a day.
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Potential Data Type Change: No alterations of data type will be needed as we will be using scatter plots as an example. However, for simpler visualisations, if time of day is represented in a continuous or timestamp format, it may need to be discretised into categorical time intervals (e.g., morning, afternoon, evening).
Question 3 - What is the trend in fatalities over the months of 2019?
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Data Attributes Needed: Month, Year, Number of fatalities. -
Data Transformation: a)
Filtering the data for the year 2019: If the dataset contains data for multiple years, it needs to be
filtered to include only the records from the year 2019.
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Potential Data Type Change: No data type is required to be changed.
HIT2316/6316 Usability
G2- 2
Swinburne University of Technology
Almyra Zahra 103148055 3
Include this file as evidence for your Demonstration 2
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