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

Questioning 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.