# reSolve: Algorithmic thinking – Data visualisation

This unit teaches students to use modern tools and methods to describe and find relationships in large, authentic, real-world datasets, including the World Bank Open Data for global development. The unit shows how computer-based information visualisation and data analysis can help us to find and to better understand complex relationships in our world. Activities follow a 'journey of discovery' that interprets raw data by applying different visualisation methods.

Year level(s) Year 9, Year 10
Audience Teacher
Purpose Teaching resource
Teaching strategies and pedagogical approaches Mathematics investigation
Keywords data representation, algorthmic thinking

## Curriculum alignment

Curriculum connections Technologies, Numeracy, STEM/STEAM
Strand and focus Statistics, Build understanding, Apply understanding
Topics Data representation and interpretation
AC: Mathematics (V9.0) content descriptions
AC9M10ST02
Compare data distributions for continuous numerical variables using appropriate data displays including boxplots; discuss the shapes of these distributions in terms of centre, spread, shape and outliers in the context of the data

AC9M10ST03
Construct scatterplots and comment on the association between the 2 numerical variables in terms of strength, direction and linearity

AC9M10ST04
Construct two-way tables and discuss possible relationship between categorical variables

AC9M9ST03
Represent the distribution of multiple data sets for numerical variables using comparative representations; compare data distributions with consideration of centre, spread and shape, and the effect of outliers on these measures

AC9M9ST05

Plan and conduct statistical investigations involving the collection and analysis of different kinds of data; report findings and discuss the strength of evidence to support any conclusions?

AC9M10ST01
Analyse claims, inferences and conclusions of statistical reports in the media, including ethical considerations and identification of potential sources of bias

Numeracy progression Interpreting and representing data (P8)