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# Statistical Literacy Units of Work

#### Units of work

Level 1

Level 1 Statistical literacy A01

• make a statement about a data display
• decide if a statement about a data display is true or false
• match a statement to the appropriate graph
Match Ups
Level 2

Level 2 Statistical literacy A01

• make a statement about a data display
• decide if they agree or disagree with a statement about the data display
• give reasons to support their evaluation of the statement
True or False
• make a statement about probabilities shown on a spinner
• evaluate statements classmates make about probabilities shown on a spinner
• provide reasons to support their evaluation of the statement
Level 3

Level 3 Statistical literacy A01

• interpret information from graphs
• make statements based on data shown on graphs
• identify the most suitable graph to show survey results
Which Graph?
 Level 3 Statistical literacy A01 Level 3 Statistical investigation A01
• interpret information from graphs
• make statements based on data shown on graphs
• identify the most suitable graph to show survey results
• construct graph using Excel
Which Graph? with Excel
Level 4
 Level 4 Statistical literacy A01 Level 4 Statistical investigation A01
• agree or disagree with a statement made about the findings of statistical investigations
• give a reason for their evaluation of the statement
• complete a statistical investigation by collecting, displaying and discussing data
Making Evaluations
These are the elaborations of the Statistical Literacy Achievement Objectives taken from the Curriculum page of the website.

#### Level One

AO1: Interpret statements made by others from statistical investigations and probability activities. This means students will match comments made by others, usually their classmates, with the features of displays. These displays will be showing category data as pictographs, set diagrams, and bar charts.

#### Level Two

AO1: Compare statements with the features of simple data displays from statistical investigations or probability activities undertaken by others. This means students will critically consider comments made by others, usually their classmates, by referring to the features of displays on which the person is making claims. These displays will be showing either category data (pictographs, bar, strip, and pie graphs) or whole number data (dot plots or stem and leaf graphs). Students should also consider whether the chosen display/s best shows patterns in the data, e.g. strip and pie graphs show proportions well, pictographs and bar graphs show differences well.

#### Level Three

AO1: Evaluate the effectiveness of different displays in representing the fi ndings of a statistical investigation or probability activity undertaken by others. This means students will learn to become critical consumers of statistically based information. This involves critically analysing the choice of display other people have made to convey statistical information. At Level Three students should be able to gain information from all of the displays mentioned in Statistical Investigation, and be aware of the type of data each display is appropriate for and the kind of pattern or relationship that the display is best at communicating. For example, pictographs, and bar graphs highlight difference between frequencies of categories, e.g. four more students have blue eyes than green, while pie charts and strip graphs highlight proportions, e.g. the spinner landed on red about one third of the time. Students should link the claims made by others with the appropriateness of the displays used.

#### Level Four

AO1: Evaluate statements made by others about the findings of statistical investigations and probability activities. This means students will critically evaluate the strength of arguments proposed by others that is supported by statistical information. At Level Four students should consider features of the statistical investigation of others in weighing the strength of the findings. These features include the appropriateness of sampling methods (e.g. number, representativeness), quality of the data collection (e.g. questions asked, accuracy of measurement, fairness of the experiment), data analysis (technology use, choice of displays) and the extent to which claims made are supported by the evidence.