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Listed under:  Mathematics  >  Statistics and probability  >  Data representation
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Data Representation

Find out about Data Representation. Use this topic from the Digital Technologies Hub to learn more, get ideas about how to teach about it, find out what other schools are doing and use the applications and games in the classroom.

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Digital systems

Find out about Digital systems. Use this topic from the Digital Technologies Hub to learn more, get ideas about how to teach about it, find out what other schools are doing and use the applications and games in the classroom.

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Systems thinking

Find out about Systems thinking. Use this topic from the Digital Technologies Hub to learn more, get ideas about how to teach about it, find out what other schools are doing and use the applications and games in the classroom.

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User interface

Find out about User interface. Use this topic from the Digital Technologies Hub to learn more, get ideas about how to teach about it, find out what other schools are doing and use the applications and games in the classroom.

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Digital Technologies Hub

The Digital Technologies Hub is a website that supports Australian primary teachers, secondary teachers, students, school leaders and school communities in engaging with the Australian Curriculum: Digital Technologies. The hub provides scaffolded support for teachers and many of the resources will assist those getting started ...

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Can AI guess your emotion?

Discuss emotions as a class, and introduce the idea of artificial intelligence (AI). This lesson can also be used to introduce image classification – a key application of AI. Developed in collaboration with Digital Technologies Institute.

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Sniffing out disease lesson

In this lesson, students consider contemporary research approaches to disease identification. First, they conduct an experiment to test how sensitive their sense of smell is and explore how our sense of smell functions. Students then learn about at how animals are trained to use their sense of smell to detect human disease. ...

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Conduct statistical investigations: Year 9 – planning tool

This planning resource for Year 9 is for the topic of Conduct statistical investigations. Students plan and conduct a statistical investigation. Encourage students to think creatively to come up with a topic for investigation; prompt students to choose a topic of interest so that they engage in the process and are motivated ...

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Interpret and discuss data displays: Year 9 – planning tool

This planning resource for Year 9 is for the topic of Interpret and discuss data displays. Students will be presented with various digital media to investigate and evaluate findings from reports of surveys. Students will make informative decisions based on their prior knowledge of sampling and data collection to make judgements ...

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Interpret and compare data displays: Year 3 – planning tool

This planning resource for Year 3 is for the topic of Interpret and compare data displays. Students create and compare different graphical representations. They interpret the data and make generalisations.

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Conduct statistical investigations: Year 3 – planning tool

This planning resource for Year 3 is for the topic of Conduct statistical investigations. Students conduct guided statistical investigations, collecting data through survey responses and other methods. They record and display data using digital tools, interpret the data and communicate their results.

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How can AI recognise what it sees?

This lesson is an introduction to the way in which a computer sees. It focuses on image recognition that involves feature extraction, object detection and classification. This lesson was developed in collaboration with Dr Karsten Schulz, Digital Technologies Institute.

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Lunch box data

Use this assessment task to explore data collection, analysis and presentation.

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Sustainable agriculture: agri-environmental indicators

This is a web resource that provides a database of agri-environmental indicators for environmental performance of agriculture in OECD countries between 1990 and 2008. The data table can be customised, with options to view by country or by theme: land, energy, air, nutrients, soil, biodiversity, pesticides, water, farm management ...

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The Sydney Metro rail project – Stage 5

This inquiry-based unit of work was created, trialled and peer reviewed as part of a professional learning program in inquiry-based learning for school teachers. The professional learning courses were part of a pilot partnership between the NSW Government’s Sydney Metro transport agency and Western Sydney University. The ...

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reSolve: Measurement - Jump!

In this sequence of two lessons, students investigate how far they can jump and explore the jumping distance of a range of animals. Students first estimate the distance they can jump, then undertake an investigation by jumping using a range of techniques. Class data is recorded and displayed and students compare their jumping ...

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Australian Historical Population Statistics to 2014 - dataset

The dataset provides statistics about the population of Australia in terms of age and sex from 1901 to 2014. It is made available by the Australian Bureau of Statistics (ABS). The dataset is in MS Excel format.

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ABS: national regional profile, 2007-2011

This is a digital resource provided by the Australian Bureau of Statistics, which can be used to investigate data relating to the economy, population and people, industry, and environment and energy of selected regions in Australia. The resource contains maps and enables a region to be searched based on a range of geographical ...

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ABS: agricultural resource management practices, Australia, 2011-12

This is a digital resource containing data on various agricultural practices used on Australian farms, and was collected in a 2011-2012 Australian Bureau of Statistics survey. This resource provides information about farming practices including pasture and crop cultivation, livestock and feral animal management, fertiliser ...

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reSolve: Monte Carlo Simulations

This sequence of two lessons explores how statistical techniques that rely on randomly generated data can be used to solve problems. In the first lesson, students compare different methods for calculating the area of an irregular shape, using the context of oil spill maps. They are introduced to the Monte Carlo method for ...