Flow of Activities
Activity Meaningful questions
How can a data set be used to answer my question?
Australian Curriculum Alignment
- Collecting, managing and analysing data (ACTDIP036)
- Collecting, managing and analysing data (ACTDIP037)
What's this about?
Students consider meaningful questions that they want to answer. They use these questions to apply their understandings about, and develop their skills of, data analysis and data visualisation.
When acquiring data, students consider whether the data set is representative of the entire audience. Some data sets may be biased as they are from a sample that does not fully represent all views.
Data acquired from a range of resources may include both quantitative and qualitative data. To effectively use qualitative data, techniques may need to be applied.
To undertake useful data analysis, students need to start with quality data. There are plenty of things that can go wrong with data; for example, data may be inappropriately structured or organised, may have formatting issues such as empty cells or apostrophes, may have spelling errors or may be numeric data imported in an incorrect format such as date or currency.
In acquiring data from a database, students should develop an understanding that data is stored in a way that allows it to be efficiently and reliably retrieved, and this is different to how it is presented.
Learning tasks
- Discuss some broad areas for inquiry that are of interest to students and that would require data to make evidence-based claims. These may be able to be integrated into a classroom context for example in English, science or geography.
- Some areas of interest:
- Social conscience (eg homelessness): Who is affected? Do we have people in our area who are homeless? What can be done to help?
- Entertainment (eg books, music or movies): What genre of music creates the most money annually and has this changed over time? Choose a favourite novel and determine which characters within the story interact the most. In the ‘Star Wars’ series of movies, who are the villains and who are the heroes; who is related and who isn’t?
- Health: What are the top ten health risks for Australians? Do certain environmental conditions trigger asthma? What factors affect life expectancy?
- Environment: What data supports climate change theory? How has the climate changed over time? What habitat is most vulnerable and which species are likely to be impacted?
- Sports: How fit does an athlete need to be to play a particular sport? Are athletes who warm up before physical activity less likely to be injured?
- Locate data sets that can be used to answer questions of interest. Data sets can be found on the internet or data can be collated from an online survey; for example, using an online survey tool such as Survey Monkey or Google Forms.
- Although not a requirement at this level, students could use a structured query language to retrieve specific data from a structured database, and compare this to ad hoc queries and search engine queries. Students could identify the advantages of different forms of queries.
- Often data needs to be cleaned up to make it useful for analysis and visualisation. Provide guidance to students on how to make sure data is in a useable form; for example, in a spreadsheet such as XLS and CSV.
Supporting Resources
Top ten ways to clean your data
This website offers ten ways to clean your data (for example, by correcting misspellings).
How does income relate to life expectancy?
In this short video Professor Hans Rosling shows that people live longer in countries with a high GDP per capita.
Choose your own statistic
This interactive website provides information about important issues by exploring different statistics about Australian society. Students can download data sets to organise and analyse data.
GovHack 2017 data
This website features a comprehensive list of the official data sets available for GovHack.
Assessment
Suggested approaches may include
- Identification of sources of data
- List of validation techniques to enhance the reasonableness of the data to be manipulated
- Examples of a coding system for qualitative data
Activity Working with data
What are some ways to organise, analyse and visualise data in a spreadsheet?
Australian Curriculum Alignment
- Collecting, managing and analysing data (ACTDIP036)
- Collecting, managing and analysing data (ACTDIP037)
What's this about?
When working with large amounts of data, tools enable the user to manage the bulk of information to get the most value from it.
Spreadsheets enable you to sort and filter data insert subtotals into sorted lists, use simple formula and visualise data.
More complex data sets may require the use of pivot tables to make it easier to analyse all of the information in your worksheet. Pivot tables help make your worksheets more manageable by summarising your data and allowing you to manipulate it in different ways.
When using large data sets, it is possible to use a programming language such as Python to read and write the data enabling analysis. To do this, data should be in CSV format, which is like Excel standard spreadsheet format, presented in plain text.
Learning tasks
- Revise various ways students can use a spreadsheet to make sense of data sets.
- Model, or use students with expertise in this skill or provide online tutorials so that all students explore how to create a pivot table.
- Once you've created a pivot table, you can use it to answer different questions by rearranging, or pivoting, the data.
- Model ways to use a pivot table or provide suitable video tutorials (some are available on YouTube).
- Creating a dashboard as part of your workbook can be used to summarise the data and present related data visually.
- Remind students that correlation does not necessarily equal causation. Spend time looking at charts where data correlates but does not have a causal link.
- Provide online tutorials or model as a lesson how to use spreadsheet software such as Excel to create a heat map by assigning a colour to numerical data and using conditional formatting.
- As a further challenge, students may incorporate data within programming; for example, using Python programming language to run a series of commands to interrogate a data set imported as a CSV.
Supporting Resources
Data analysis
Learn how to use the following functions in Excel: sort, filter, conditional formatting, charts, pivot tables, tables and what-if analysis. Also learn about the Analysis ToolPak add-in.
Tips and tricks for working with data in Excel
This video will help you learn about creating a chart, importing a data set from a website, sorting and filtering, conditional formatting and pivot tables.
Correlation and causality
This is a Khan Academy lesson about correlation and causality.
Python library: CSV file reading and writing
This support is provided by Python and provides guidance on how to use Python to read and write data from an Excel data file.
Python for beginners: Reading and manipulating CSV files
This blog post provides a useful, easy-to-understand tutorial on how to use Python to read and write data from an Excel data file.
Import data and analyse with Python
This tutorial is a basic step-by-step introduction on how to import a text file (CSV), perform simple data analysis, export the results as a text file, and generate a trend.
Lesson Ideas
A spreadsheet’s secret weapon
This lesson helps students learn to use pivot tables, which have been described as the most powerful tool within spreadsheets.
Seeing the wood for the trees
In this lesson sequence students summarise data using advanced filtering and grouping techniques; for example, pivot tables in spreadsheets and aggregation functions in databases.
Assessment
Suggested approaches may include
- Presentation or demonstration
Activity Channels of information
How does data visualisation help us identify patterns in a data set?
Australian Curriculum Alignment
- Collecting, managing and analysing data (ACTDIP037)
What's this about?
Data can be encoded and represented visually as channels of information. These visual channels include spatial position, colour, size, shape, orientation and direction of motion. Multiple visual channels can be used to simultaneously represent data.
Heat maps are a way of visualising numerical data represented as colour. Interactive data visualisations help further to model processes and examine relationships.
Learning tasks
- After a brief discussion about data visualisations and what they are, provide students with a set time to use the internet to locate a visualisation that appeals to them. Share as a class and ask generic questions such as:
- What information does the visualisation convey?
- What is done well; what is misleading?
- What channels of information are used; for example, size, colour, position etc?
- Examine a numeric data set shown in a table compared with an analysis based on colour; for example, numerical data such as temperatures, moisture levels and ocean depth.
- Many other types of numerical data can be effectively used; for example, retail data and population data – in fact, any data that is within a range where colour can be used to represent the values in that range. Let students explore a data set of interest and report back their findings.
- Provide access to relevant tools that enable users to visualise data on a map; the data set will need to contain location data such as latitude and longitude, countries/regions, states, counties or postal codes.
- Analyse population data made up of structured data categorised as, for example, income ($), life expectancy (years), population (millions of people), country (name), age (years) etc. Examine the relationships using visualisation tools such as those provided by Gap Minder.
Supporting Resources
Tableau Desktop Public Edition
Create graphs, charts, maps and more. Tableau Public is a popular, free data visualisation tool.
Gap minder tools
Gap Minder’s visualisations tools can be used to interrogate population data.
Turn your data into a heat map
This short article provides tips about how to use conditional formatting to turn a data set into a heat map.
Census 2016: This is Australia as 100 people
This data visualisation shows what Australia’s data would look like if Australia were 100 people.
Create a map chart
You can use a map chart to compare values and show categories across geographical regions. Use it when you have geographical regions in your data, such as countries, states or postal codes.
How to create a cool heat map in Excel
This video tutorial goes through the process of how to use conditional formatting to turn a data set into a heat map.
Creating heat maps with Excel
While this video draws on a Chicago data set, it provides a useful tutorial clearly explained about how to use location data and use the map function in Excel.
Create a map in power view
Create a 3D map of your data in Excel.
Assessment
Suggested approaches may include
- Artefact analysis
Activity Presenting information
How can I present data effectively as information?
Australian Curriculum Alignment
- Collecting, managing and analysing data (ACTDIP036)
- Collecting, managing and analysing data (ACTDIP037)
- Investigating and defining (ACTDIP038)
What's this about?
Both the appearance and functionality of information contribute to its quality. Appearance relates to the aesthetics of information and it usually draws on design principles, such as alignment, repetition, contrast, space and balance. Alignment connects elements visually through an invisible line. Contrast shows differences between elements. Repetition involves re-using the same or similar elements for consistency. Space relates to the distance between elements. Balance relates to the weighting given to different elements.
Functionality also contributes to the effectiveness of information. Characteristics of functionality include the useability of a solution such as its flexibility and ease of use, and accessibility such as its ease of navigation.
The quality of information is also enhanced if conventions (or normally accepted procedures) are applied such as a chart having a legend, heading and labelled axes. Similarly, the use of colour should promote contrast but also consider users who are colour blind.
Learning tasks
- After analysing the data students can create their own infographic to present their ideas visually.
- Students create a structured database of something of interest; for example, games, sporting teams, digital photographs, music, etc.
- Students implement methods of validating data as it is entered, using data types, range and constraints, codes and cross-referencing. Students implement various checks from the wide range available and compare their effectiveness in reducing data errors.
Supporting Resources
Canva
Create infographics with Canva's free online infographic maker.
Zoho
Build applications to collect and organise your data online with an easy-to-use database management software.
Sodadb (Simple Online Database)
Simple Online Database offers templates to assist students with databases.
Intro to SQL: Querying and managing data
Use this Khan Academy tutorial to learn how to use Structured Query Language (SQL) to store, query and manipulate data.
Design your own database: Concept to implementation * PDF seems to have been removed couldent find new location
This PDF describes how to design a database without
touching a computer.
SQLZoo
This is a series of SQL tutorials and activities.
Introduction to Oracle SQL course
Use this course to learn SQL which uses Oracle Express as the database used for this course.
Assessment
Suggested approaches may include
- Presentation or demonstration
- Artefact analysis
