How do psychologists analyse and present the data they collect?
Analysing and presenting data: qualitative and quantitative data, descriptive statistics including measures of central tendency and dispersion, methods of presenting data, and drawing conclusions from research findings.
The SQA Higher Psychology research content on data: the difference between qualitative and quantitative data, descriptive statistics such as the mean, median, mode and range, methods of presenting data in tables and graphs, and how psychologists draw and justify conclusions from findings.
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What this dot point is asking
Once data are collected they must be analysed and presented. The SQA wants you to know the difference between qualitative and quantitative data, the main descriptive statistics (measures of central tendency and dispersion), how to present data in tables and graphs, and how to draw justified conclusions. This is examined directly and is needed for the analysis section of the assignment.
The answer
Qualitative and quantitative data
Measures of central tendency
Measures of dispersion
Presenting data and drawing conclusions
Examples in context
The course studies show why analysis choices matter. Reporting Milgram's finding as " obeyed fully" uses a simple numerical summary of quantitative data. Asch's conformity rate (about a third of critical trials) is likewise a quantitative summary that allows comparison across conditions. Stress and relationship studies that use interviews produce qualitative data, rich in detail but needing careful interpretation rather than a single number. Correlational studies, such as linking life events to illness, are presented on scattergrams and must be reported as relationships, not causes, which is the most common analysis point examiners reward. Selecting the right statistic and presentation, and drawing a conclusion the data actually support, is the skill assessed here and in the assignment.
Try this
Q1. Name the three measures of central tendency. [3 marks]
- Cue. The mean (average), the median (middle value) and the mode (most frequent value).
Q2. Explain why a scattergram is used for correlational data, and what a conclusion from it may and may not claim. [4 marks]
- Cue. A scattergram shows the relationship between two measured variables; the conclusion may state that they are related but must not claim that one causes the other.
Exam-style practice questions
Practice questions written in the style of SQA exam questions on this dot point, with worked answer explainers. The year tag is the paper they imitate, not the source.
SQA Higher (research)6 marksExplain the difference between qualitative and quantitative data and give an example of each.Show worked answer →
A -mark question testing research knowledge. Markers want clear definitions and a fitting example of each.
Quantitative data is numerical, such as a score on a memory test or the number of times a behaviour occurs; it is easy to analyse statistically and compare. Qualitative data is non-numerical and descriptive, such as what a participant says in an interview about their experience of stress; it is rich and detailed but harder to summarise. Explaining the trade-off, depth versus ease of analysis, raises the mark.
SQA Higher (research)6 marksDescribe the mean, median and mode and explain when the median might be preferred.Show worked answer →
A -mark question. Markers reward accurate definitions and a reason for choosing the median.
The mean is the arithmetic average (add the values, divide by how many); the median is the middle value when the data are ordered; the mode is the most frequent value. The median may be preferred when the data contain extreme scores (outliers), because these distort the mean but not the median, so the median better represents a typical value in a skewed set.
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Sources & how we know this
- SQA Higher Psychology Course Specification — SQA (2019)
- SQA Higher Psychology: guidance on creating assessments — SQA (2019)