Data cards are a way of storing data about a person, object or non-physical entity. When using data cards each individual data card represents one person, object or non-physical entity. Data information for each person, object or non-physical entity is recorded in the same way to make future analysis more straightforward. Information from data cards can also be recorded into a spreadsheet for analysis to be made using statistical software.

Data cards can provide secondary data, as many of the examples given here show.�� They can also be used for collecting data, CensusAtSchool data collection information usually has a data card for students to record their measurements on. The data card shown here is from the 2025-2026 CensusAtSchool questionnaire primary teachers guide page 5.

Year 1-3 Data Cards

Three sets of data cards with 7 or 8 variables. The 25 “students/children” are from the CensusAtSchool 2023 database. They are a random selection of year 3-6 students/children from across Aotearoa New Zealand, and the same students/children are used in the three sets of data cards.

Teaching and learning activities associated with the year 1-3 data cards are .

Year 4-6 data cards

The year have 14 variables. The 74 “students/children” are from the CensusAtSchool 2025-2026 database. They are a random selection of year 4-6 students/children from across Aotearoa New Zealand.

Variables included:

• Height
• Gender �� �� �� �� �� �� �� �� �� �� ��
• Hair colour�� �� �� �� �� �� �� �� ��
• Eye colour
• Languages spoken
• Favourite colour��
• Year level
• Plays a musical instrument
• Has pets
• Has broken a bone
• Travel method to school
• Time taken to get to school
• Left foot length
• Right foot length

Teaching and learning activities associated with the year 4-6 data cards are .

Year 7-8 data cards – to come

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Dinos of patagonia data cards

Variables:

The data is also available in a CODAP document |

You can use the blank data cards to find out information about other dinosaurs. If you want to add the new dinosaurs to the dataset, then make a copy of this and add them in.

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Vaires-sur-Marne Nautical Stadium

A set of data cards for the 2024 New Zealand Olympic Team – 32 athletes who are competing at the Vaires-sur-Marne Nautical Stadium. The data was sourced from the .

Find out about individual athletes by typing their names in the search bar. You can filter by Games Type (Olympic Summer Games), and Sport to find the athletes in a sport or group of sports.��

The will host the Olympic rowing and canoe-kayak events.

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

• Make a set of data cards for another sport or group of sports.
• Make a set of data cards for a
• Add variables to the existing set of data cards, e.g., the Olympian number, where they are based, did they compete in the Youth Olympics, what year was their Olympic debut

All the data that is in the data cards is also in the CODAP document listed in the resources.

Variables in the data card set provided:

This activity explores the following key ideas:

• Using existing data to undertake a statistical enquiry

Resources

• Teaching Notes
• Olympics NZ – Rowing, Canoe Kayak Sprint, Canoe Kayak Slalom data cards
• – Olympics NZ – Rowing, Canoe Kayak Sprint, Canoe Kayak Slalom
• Blank data cards – make your own set of NZ Olympic Athlete data cards

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The following interrogative questions provide a good starting point to understand the data, what was collected, how it was collected and who it was collected from (Arnold, 2022, p. 90).

Overall for the dataset:

1. Was the data collected using an observational study or an experiment (from year 9)? (1. Method)
2. Who was the data collected from? (2. “Who”)
3. Who collected the data? (1. Method)
4. When was the data collected? (1. Method)��
5. Where was the data collected? (1. Method)
6. What was the purpose for collecting the data? (Initial investigator’s problem/purpose)

Specific to the variable (3. What and how):

1. State the variable.
2. What was the data collection or survey question asked to collect the data?��
3. How was the variable measured?
4. What are the units, if any, for the variable?
5. What are the possible outcomes for the variable?
6. What type of data is it? Categorical or numerical?

Arnold, P. (2022). Statistical Investigations | Te Tūhuratanga Tauanga. NZCER Press.��

The at North Carolina State University have created this that provides an expanded set of interrogative questions when using data from other sources.

In our modern society, data is generated all the time and in various ways. Sometimes we create our own data from experiments, surveys, etc. More often, we use data generated from other sources, available online. At this time, data is even generated automatically, as in click-log data and other metadata, collected as we go about our daily lives. But all data has context. To gain a deeper understanding of data from other sources, you must examine the context. The questions below provide guidance to make sense of a dataset. You do not need to answer each of these questions. They are intended to guide you in developing a data interrogation mindset, wherein a good understanding of data and its sources will inform your analysis and claims made with the data.

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Data card from the Primary Teacher Guide CensusAtSchool 2023, p. 38

What are Data Cards?

Data cards are a way of storing data about a person, object, or non-physical entity. When using data cards each data card represents one person, object, or non-physical entity.

Data information for each person, object, or non-physical entity is recorded in the same way to make future analysis more straightforward. Information from data cards can also be recorded into a spreadsheet for analysis to be made using statistical software.

Data cards can provide secondary data, as many of the examples given here show.�� They can also be used for collecting data, CensusAtSchool data collection information usually has a data card for students to record their measurements.

Year 1-3 Data Cards

Three sets of data cards with 5 or 6 variables. The 25 “students/children” are from the CensusAtSchool 2023 database. They are a random selection of Year 3-6 students/children from across Aotearoa New Zealand, and the same students/children are used in the three sets of data cards.

Year 4-6 Data Cards

The Year 4-6 data cards have 14 variables. The 78 “students/children” are from the CensusAtSchool 2023 database. They are a random selection of Year 4-6 students/children from across Aotearoa New Zealand.

Variables included:

• Gender
• Year level
• Hair colour
• Hair type
• Eye colour
• Languages spoken
• Handedness
• Cats or dogs
• Height
• Pineapple on pizza
• Standing jump
• Right foot length
• Travel method to school
• Travel time to school

Year 7-8 Data Cards

There are two sets of Year 7-8 data cards, each with 12 variables. The 79 “students” are from the CensusAtSchool 2023 database. They are a random selection of Year 7-8 students from across Aotearoa New Zealand.

Making Data Cards Using Your Class CensusAtSchool Data

A Google Sheet has been created that can be used to make data cards from your returned class data when your class has completed the CensusAtSchool questionnaire.

It includes an instruction tab for making the data cards, three tabs to support making the data cards, and an instruction tab for printing.

Using Data Cards

Data cards are a good way of introducing students to using secondary data. They allow for hands-on activities such as making data visualisations to analyse the data for an investigative question. The complexity of the data cards should change depending on the year level aimed at. The CensusAtSchool 2023 database data cards are examples using secondary data.

Whether the secondary data is provided by the teacher or sourced by the students, the information required for understanding about the data collection is within the information we refer to as the contextual knowledge about the dataset. Contextual knowledge includes:

• The group or population that the data was collected from
• When, where and how the data was collected
• The original purpose for collecting the data

“Planning” for secondary datasets includes interrogative questions to help with developing a deep understanding of the data that would be available to use. The “overall for the dataset” interrogative questions in the next section help us with understanding about the data collection and align with the contextual knowledge ideas listed above. Regardless of whether the teacher provides the data or the students source the data themselves, contextual knowledge is important. The “overall for the dataset” interrogative questions also include who the data was collected from (adapted from , p. 90).

The final part of finding out about the secondary dataset, the data cards, is to identify and interrogate the variables in the dataset. To do this the “specific to the variable” interrogative questions in the next section are used.

PLAN/DATA: Interrogating secondary datasets

It is good practice to interrogate any secondary datasets that are used with students. Depending on what you are trying to achieve, it could be built into the teaching and learning sequence, or it could be background research you do before using the dataset with students.

The following interrogative questions provide a good starting point to understand the data, what was collected, how it was collected and who it was collected from.

Overall for the dataset:

1. Was the data collected using an observational study or an experiment (from year 9)? (1. Method)
2. Who was the data collected from? (2. “Who”)
3. Who collected the data? (1. Method)
4. When was the data collected? (1. Method)
5. Where was the data collected? (1. Method)
6. What was the purpose for collecting the data? (Initial investigator’s problem/purpose)

Specific to the variable (3. What and how):

7. State the variable.
8. What was the data collection or survey question asked to collect the data?
9. How was the variable measured?
10. What are the units, if any, for the variable?
11. What are the possible outcomes for the variable?
12. What type of data is it? Categorical or numerical?

(, p. 79)

The CensusAtSchool 2023 database data cards should be interrogated before they are used by students so that they become familiar with the variables that are available for each data card set.

Two useful documents to support this are the 2023 CensusAtSchool questionnaire, and the 2023 variable list.

PROBLEM: Posing investigative questions

When we start with a provided dataset, for example, using the CensusAtSchool 2023 database data cards, the way we work through the PPDAC cycle is different from when we are collecting primary data.

Using the statistical enquiry cycle for a provided dataset may follow the approach shown in Figure 4.10 below.

Figure 4.10. The statistical enquiry cycle for provided datasets (, p. 159)

Investigative questions are posed once the data has been interrogated and students understand the variables which are available in the dataset, and who the data was collected from.

ANALYSIS: Creating & describing data visualisations

Early data visualisations can be made with data cards, from year 1 students can sort and order the data cards to summarise data. Data cards are an enactive mode (Bruner, in Graham, 2006), where students are manipulating objects and building spatial awareness. Data cards are foundational to dot plots, bar graphs, histograms, scatter plots and two-way tables. They can be used in summary, comparison and relationship situations. For more on the development of these types of data visualisations see Statistical investigations | Te Tūhuratanga Tauanga () analysis chapter – dot plots pp 229-237; bar graphs pp 237-243; histograms pp 254-248; scatter plots pp 275-280; two-way tables pp 266-271.

Examples below using the different data cards.

Y1-3 sorted by travel method to school

Y1-3 sorted by hair colour

Year 4-6 (year 6 only) travel method to school

Year 4-6 (year 6 only) hair colour

Year 7-8 data cards – set 1 – sorted by height (5 cm intervals)

Year 7-8 data cards – Set 2 – sorted by bed time

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This resource compiles a list of datasets for use by New Zealand teachers and students, fostering statistical and mathematical thinking. Just as the media coverage conceals layers of statistics and maths, this compilation connects you to key local and international sources. These include the New Zealand Statistical Association, the International Statistical Institute, and global hubs. Dive into a plethora of datasets, complemented by vivid graphics and encompassing health, economic, and social data.

Presented by the New Zealand Statistical Association’s Education Committee, this document empowers teachers and students to unearth statistical insights within contexts that resonate with them. The New Zealand Statistical Association’s Education Committee is providing this document, with the intention that teachers and students will find useable datasets.

Compiled by Amy Renelle, September 2023

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The Oceans of Data Institute at EDC has compiled a list of��. From National Geographic to NASA, there is something for everyone.

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