AQA Large Data Set Practice Test

When predicting future trends from large data sets, the key idea is that forecasts are not exact and must account for what could change. You should note uncertainties and potential shifts because future conditions may differ from the past that the data reflect. Uncertainty comes from sampling error, measurement limitations, and the assumptions built into models, while potential shifts arise from changes in relationships over time, such as behavior, technology, or policy. Because of this, it’s best to consider multiple plausible outcomes, report prediction or confidence intervals, and include caveats or scenario analyses rather than presenting a single fixed forecast. Focusing only on confident outcomes or ignoring variability would mislead, and setting fixed future scenarios without caveats ignores the real possibility of change.