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A set of 26 data cards and for the All Whites FIFA World Cup 2026.

The data was sourced from , , , and . There is space for students to add or draw an image for each player.Ìý

See information about using data cards for ideas on what to do with the data cards.

This activity explores the following key ideas:

• Using existing data to undertake a statistical enquiry

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In this workshop participants use CODAP (Common Online 91ÇÑ×Ó Analysis Platform) to develop ideas for two statistical concepts.Ìý The median and box plots.ÌýÌý

This activity explores the following key ideas:

• Finding the middle of a dataset and connecting this to the median.
• Finding the middle 50% of a dataset, describing this.
• Using the middle 50% and median to build a box plot.
• Recognising the quarters within the box plot.

Resources

CODAP

Related teaching and learning activities on 91ÇÑ×ÓÌý

• – Finding the middleÌý

Related teaching and learning activities on T�hūrangi

• Ìý

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Getting Started

• (See also intro videos from the and the Statistics Teachers Day)
• and

Exercises

Videos

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It was wonderful seeing so many teachers at last year’s Statistics Teachers’ Day in Auckland. Planning is already underway for this year’s event!

Later this year, we’ll let you know the overarching theme and put out a call for workshops and talks.

In the meantime, save the date:

Statistics Teachers’ Day 2026
Friday November 27

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Note: This information is being updated.

Years 1–10

Years 11–13 (Current 2007 version; curriculum being updated)

• : , , , , , , , , , ,
• For Year 13 students intending to study Statistics at the tertiary level: the Department of Statistics at the University of Auckland strongly recommends AS3.9 (Investigate Bivariate Measurement 91ÇÑ×Ó), AS3.10 (Use Statistical Methods to make a Formal Inference), and AS3.13 (Apply Probability Concepts in Solving Problems)
• NZSA Statements and Resources

Historical Record

• 2007 NZ Statistics Curriculum
  • Key Ideas: Statistical Literacy, Statistical Investigations,ÌýProbability

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The materials were developed in conjunction with and trialled by Auckland Girls’ Grammar School, Lynfield College, and Northcote College mathematics and statistics departments.ÌýÌý

The summary investigation lessons are based on students undertaking a statistical enquiry to find out about the class or year level.Ìý Lessons 1, 2, 5, 6, 9, 10, 11 broadly follow a statistical enquiry using the PPDAC cycle; this is noted in each lesson.Ìý Lessons 3, 4, 7, and 8 are concept development lessons, timed to allow for data collection and data entry across a year level cohort for the statistical enquiry.

This teaching sequence covers the following statistical concepts:Ìý

1. 1. investigate multivariate data situations for observational studies by
      
      1. exploring areas of interest (Lesson 1)
      2. posing summary investigative questions (Lesson 7, 9)
      3. make conjectures or assertions about expected findings (Lesson 4, 7, 9)
   2. plan how to collect or source data to answer investigative questions, includingÌý
      
      1. identifying the variables needed to answer the investigative questionÌý (Lesson 2)
      2. planning how to make valid and reliable measures for the variables (when collecting) or finding out how they were collected (when sourcing) (Lesson 2, 7)
      3. identifying the group of interest or who the data was collected from (Lesson 2, 7, 9)
      4. using a set of interrogative questions that check the different ethical practices that should be considered through the entire statistical enquiry cycle, including checking data collection and survey questions before testing with peers (Lesson 2)
   3. collect or source data including (Lesson 6)
      1. making decisions about the validity of data and making simple edits (cleaning data) if appropriate (Lesson 5)
      2. creating a data dictionary (collected data) or finding the metadata (sourced data) (Lesson 2, 5, 7)
   4. create, describe and reason from data visualisations to support answering the investigative question, including
      1. using multiple visualisations to provide global and local views of the data (Lesson 3, 4, 6, 7, 9, 10)
      2. identifying relevant features in distributions (Lesson 3, 4, 6, 7, 8, 9, 10) – interweaving the context in the description of the distributionÌý
   5. communicate findings, using evidence from analysis, provide possible explanations for findings, reflect onÌý conjectures or assertions, and evaluate the approach for the different phases of the statistical enquiry (Lesson 11)
   6. examine the data-collection methods and findings of others’ statistical investigations to see if their claims are reasonable, and critically consider data visualisations to see if they support or misrepresent the data (Lesson 12)

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