Statistics Teachers’ Day takes place at Auckland University, where stats education researchers, PhD students, and practising statisticians share what they are discovering in data. Teachers also share their classroom practice and resource development, modelling excellent teaching and learning with and about data on the day.

Resources

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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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Participants analysed articles using the frameworks provided (). Further online data literacy resources developed for the TFC (Tertiary Foundation Program) at the University of Auckland are also included. They could be repurposed for Level 2/3 Statistics or Scholarship programs as a weekly focus on developing students’ data literacy capabilities.

Have students select and design their own online data literacy resource, then send in resources to share.

Resources

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Statistics Teachers’ Day takes place at Auckland University, where stats education researchers, PhD students, and practising statisticians share what they are discovering in data. Many teachers also share their classroom practice and resource development, modelling excellent teaching and learning with and about data on the day.

Resources

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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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