Analysing and evaluating research: organising and presenting data, handling economic data (percentage change and index numbers), assessing the reliability and validity of sources, referencing, drawing supported conclusions, and evaluating the research process.

What this key area is asking

Having planned and gathered evidence, the second research skill is to make sense of it. The SQA expects you to "explain and use approaches to organising and referencing findings from the research gathered, and in evaluating the research process". This dot point covers organising and presenting data, the core data-handling skills (percentage change and index numbers), judging reliability and validity, referencing, drawing supported conclusions, and the distinctive Advanced Higher requirement to evaluate your own research. All of this is assessed in the project.

Organising and presenting data

Raw evidence has to be organised so it can be analysed and so the reader can follow the argument:

• Tables to set out figures clearly.
• Charts and graphs (bar charts, line graphs, pie charts) to show patterns, trends and comparisons.
• Clear labelling of axes, units, sources and time periods.

Presentation should serve the analysis, illustrating the points being argued, not decorate the report. Each table or chart should be referred to and interpreted in the text.

Handling economic data

Two calculations recur throughout economics and the project.

Index numbers (such as the Consumer Prices Index) let you compare changes over time and across different series on a common scale, regardless of the original units. Always interpret the figure, not just calculate it: say what the percentage change or index value means for the issue.

Reliability and validity of sources

Triangulating (cross-checking several independent sources) strengthens confidence. For primary data, a small or unrepresentative sample weakens reliability, which the project should acknowledge.

Referencing findings

Findings must be referenced to credit the sources and let the reader check them:

• Cite the source, author or organisation, title and date for each piece of evidence.
• Use a consistent referencing style throughout, with a list of sources at the end.
• Referencing is part of academic integrity and is assessed; unreferenced evidence is weaker and risks plagiarism.

Drawing a supported conclusion

The analysis must lead to a conclusion that answers the aim and is supported by the evidence gathered, not by assertion. A strong conclusion weighs the evidence on both sides, applies economic theory, and reaches a clear, qualified judgement.

Evaluating the research process

A distinctive Advanced Higher requirement is to reflect critically on your own research:

• The limitations of the data and methods (small or biased samples, data gaps, out-of-date figures).
• What could have been done better (a larger sample, additional sources).
• How confident the conclusion can be, given those limits.

This shows you understand the strengths and weaknesses of your own evidence, qualifies the conclusion appropriately, and is explicitly rewarded in the marking. It is also a hallmark of degree-level research.

Worked example: interpreting an index

Why this matters

Analysing and evaluating evidence is what turns gathered data into a persuasive, well-supported project, the second half of the research-skills area and a third of the course marks. Data handling (percentage change and index numbers) also appears in the question paper's data-response questions, so these skills are doubly examined. The self-critical evaluation of the research process is exactly the analytical maturity the SQA, and university study, expects of an Advanced Higher candidate.

Try this

Q1. A wage index rises from 100 to 108. Calculate the percentage change and state what it means. [2 marks]

• Cue. $\dfrac{108 - 100}{100} \times 100 = 8\%$: wages are 8 per cent above the base-year level.

Q2. Give two things to consider when judging whether a source is reliable. [2 marks]

• Cue. Any two of: who produced it and why (possible bias), how recent the data is, how it was collected (sample size and method), and whether other sources corroborate it.