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WS03 - Predict a winner

Mathematics, Year 10

By the end of Year 10, students recognise the effect of approximations of real  numbers in repeated calculations. They use mathematical modelling to solve problems involving growth and decay in financial and other applied situations, applying  linear,  quadratic and exponential functions as appropriate, and solve related equations, numerically and graphically. Students make and test conjectures involving functions and relations using digital tools. They solve problems involving simultaneous linear equations and linear inequalities in 2 variables graphically and justify solutions. 

 

Students interpret and use logarithmic scales representing small or large quantities or change in applied contexts. They solve measurement problems involving surface area and volume of composite objects. Students apply Pythagoras’ theorem and trigonometry to solve practical problems involving right-angled triangles. They identify the impact of measurement errors on the accuracy of results. Students use mathematical modelling to solve practical problems involving  proportion and scaling, evaluating and modifying models, and reporting assumptions, methods and findings. They use deductive reasoning, theorems and algorithms to solve  spatial problems. Students interpret networks used to represent practical situations and describe connectedness 

 

They plan and conduct statistical investigations involving bivariate data. Students represent the distribution of data involving 2 variables, using tables and scatter plots, and comment on possible association. They analyse inferences  and conclusions in the media, noting potential sources of bias. Students compare the distribution of continuous numerical  data  using various displays, and discuss distributions in terms of centre, spread, shape and outliers. They apply conditional probability  to solve problems involving compound events. Students design and conduct simulations involving conditional probability, using digital tools. 

Statistics

AC9M10ST01

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

Statistics

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

Statistics

AC9M10ST03

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

Statistics

AC9M10ST04

construct two way tables and discuss possible relationship between categorical variables

Statistics

AC9M10ST05

plan and conduct statistical investigations of situations that involve bivariate data; evaluate and report findings with consideration of limitations of any inferences

Annotations

 

1. Demonstrates an understanding of terms used to describe the distribution of data. 

 

2. Describes the numerical variables chosen to analyse comparatively.

3. Describes how to determine the distribution of data in terms of centre and spread. 

 

4. Acknowledges and discusses the reasonableness and limitations of this method.  

5. Chooses to use a spreadsheet to represent the numerical data, and creates and uses an algorithm to calculate the average weekly income. 

 

6. Determines the distribution of data in terms of centre and spread. See also 12, 17 and 23.  

 

7. Creates a line graph to represent numerical data, using digital tools. 

 

8. Discusses the distribution of data in terms of shape.

9. Creates a scatterplot to represent bivariate data, using digital tools. 

 

10. Represents data in a comparative display, using digital tools. See also 21. 

 

11. Interprets data represented in a scatterplot and comparative display. 

 

12. Determines the distribution of data in terms of centre and spread. See also 6, 17 and 23. 

 

13. Creates a horizontal bar chart to represent data, using digital tools. See also 24.

14. Creates a histogram to represent the continuous numerical data, using digital tools. 

 

15. Determines the distribution of data in terms of spread. 

 

16. Interprets data displays and describes the distribution in terms of shape. 

 

17. Determines the distribution of data in terms of centre and spread. See also 6, 12 and 23. 

 

18. Represents the data in a line graph, using digital tools. 

19. Interprets data represented in displays and describes the distribution in terms of shape. 

 

20. Represents data in a scatter plot, using digital tools. 

 

21. Represents data in a comparative display, using digital tools. See also 10. 

 

22. Interprets the data displays and compares results, making inferences.  

23. Determines the distribution of data in terms of centre and spread. See also 6, 12 and 17. 

 

24. Creates a horizontal bar chart to represent data, using digital tools. See also 13. 

 

25. Creates a histogram to represent the numerical data, using digital tools. 

 

26. Interprets displays and describes the distribution in terms of shape.

27. Makes a prediction based on statistical analysis. 

 

28. Justifies prediction based on data represented in scatterplots created using digital tools. 

 

29. Creates scatterplots to represent data, using digital tools. 

 

30. Compares data and describes the distribution of data in terms of shape.

31. Creates comparative displays to represent data, using digital tools. 

 

32. Describes and compares the distribution of data in terms of centre and shape. 

33. Draws conclusions based on the interpretation of data acquired and analysed as part of a statistical investigation.