Analysing statistical data on two economic issues (internal)
Internal 4 credits Data processing Trends Relationships Inter-relationships ForecastingAS 91226, 4 credits. THREE distinct required components, not two: process/present data for TWO issues to show trends, explain the relationships WITHIN each issue's data, AND explain the INTER-RELATIONSHIP BETWEEN the two issues. Excellence is a specific, different task from a generic "comprehensive analysis": a justified forecast built from extrapolating both data sets.
1 Reading the notation
Three components at Achieved, not two — and an Excellence task that is a specific forecast, not a general evaluation.📖 Terms the schedule grades you on
4 terms- Analyse (Achieved)
- Process/present data for two issues to show trends; explain relationships in EACH; explain the INTER-RELATIONSHIP between them.
- In depth (Merit)
- DETAILED explanations of both the within-issue relationships and the inter-relationship.
- Comprehensively (Excellence)
- A JUSTIFIED FORECAST for one issue, using EXTRAPOLATED data from BOTH issues.
- Contemporary economic issues (note 4)
- Inflation, international trade, economic growth, unemployment, or another scarce-resource-allocation issue.
2 Processing and presenting each issue's data
Processed, sourced, and presented with the right graph type for the job.What the report must contain, per issue
- The issue named, and why it matters now.
- Data with its source and dates, PROCESSED — percentage change, index, or moving average.
- A presentation whose type suits the job, fully labelled.
3 Within-issue relationships, and the inter-relationship between issues
Two distinct explanatory tasks — do not let the second collapse into a repeat of the first. ✕Treating the inter-relationship as optional extra colour
A report that explains each issue's trend well but never explicitly connects the TWO issues' data to each other has not evidenced a named, separate Achieved component. The inter-relationship needs its own explicit explanation, using a model, distinct from either issue's standalone trend.4 The Excellence-level forecast
A justified forecast built from extrapolating BOTH data sets — not a generic "limitations and judgement" discussion.What the forecast needs
- A stated extrapolation of the trend in each series.
- The inter-relationship between the two issues used to inform the forecast.
- The assumption behind the extrapolation, stated explicitly.
- A single forecast value or direction for ONE named issue.
Practice
Recall it first, then use it — testing yourself builds the memory, where rereading the notes above only feels easier.
Recall and application shuffled together — you have to work out what each item wants before you can answer it, which is the part the exam actually tests. Both kinds feed the same spacing schedule, so anything you miss comes back sooner.
Say the answer out loud before flipping — that attempt is where the learning happens, even when you get it wrong.
Exam-style only. Instant feedback, shuffled each attempt, best score saved on this device.