Mathematics / Year 10 / Statistics

Curriculum content descriptions

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

Elaborations
  • discussing the difference between association and cause and effect, and relating this to situations such as health, diversity of species and climate control
  • using statistical evidence to make, justify and critique claims about association between variables, such as in contexts of climate change, migration, online shopping and social media
  • informally using a line of good fit by eye to discuss reliability of any predictions
  • exploring how scatter plots and association help data scientists gain insights into the data, identify relationships, and can be applied to machine learning to make informed decisions about feature engineering and assess model performance
  • investigating artificial intelligence systems that analyse bivariate data to forecast or make predictions based on association using correlation analysis and discussing limitations; for example, the artificial intelligence may not capture the causality between variables or account for the contextual or ethical implications
  • investigating the relationship between \(2\) variables of spear throwers used by First Peoples of Australia by using data to construct scatterplots, make comparisons and draw conclusions
General capabilities
  • Critical and creative thinking Critical and Creative Thinking
ScOT terms

Bivariate analysis,  Scatter plots

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TIMES Module 8: Statistics and Probability: data investigation and interpretation, year 10 - teacher guide

This is a 29-page guide for teachers. Box plots are introduced as another graphical tool and are used for comparisons of data. Scatter plots are used to explore relationships between quantitative (usually continuous) variables.