How should you assess the credibility of data in the Large Data Set?

• A. Check the source (AQA), date, methods, and stated limitations; treat it as high-quality data from official statistics.
• B. Assume data from government agencies is always correct.
• C. Rely only on the most recent data point, regardless of method.
• D. Compare a single data point with your expectations.

Answer: (A)

Assessing credibility comes from examining how the data was produced. For the Large Data Set, you should look at the source (it’s from AQA and official statistics), the date it was published, the methods used to collect and process the data, and any limitations or uncertainties the producers note. This combination tells you how reliable and appropriate the data is for your analysis, and it helps you spot biases or gaps so you don’t misinterpret results. Even data from government or official bodies isn’t perfect, so it’s important to check the methodology and limitations rather than assuming it’s flawless. Focusing only on the most recent data point or comparing a single value to your expectations ignores the wider context and uncertainty, which can lead to faulty conclusions. So, the best practice is to review the metadata—source, date, methods, and stated limitations—and use that to judge trustworthiness and suitability for your work.