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IB DP Psychology — Research Methodology | SL & HL | Paper 3
🎯 Learning Intentions By the end of this note, you will be able to:
- Define descriptive statistics, measures of central tendency, and measures of dispersion using IB-aligned terminology.
- Explain the difference between the mean, median, and mode, and identify when each is the most appropriate measure to use.
- Describe the role of range and standard deviation in summarising the spread of data in a psychological study.
- Evaluate the strengths and limitations of different descriptive statistics in the context of psychological research.
- Apply descriptive statistics to a given data set or research scenario, selecting and justifying the most appropriate measure.
- Analyse how the choice of descriptive statistic can affect the interpretation of psychological findings, using concept areas such as Measurement, Bias, and Causality.
- Construct and interpret simple tables and graphs used to display descriptive data in psychological research.
Introduction & Context
Imagine a teacher returns a set of test results to a class of thirty students. Rather than reading out every single score, she says: "The average was 68 out of 100." In a single number, she has communicated something meaningful about the whole group. But a student who scored 67 might feel reassured, while another who scored 65 might feel they performed poorly — even though both are close to the same value. The question is: does that one number really tell the whole story?
Psychologists face exactly this challenge every time they collect data. A study might produce dozens, hundreds, or even thousands of individual data points. To make sense of those numbers — and to communicate findings clearly to other researchers — psychologists use a set of mathematical tools called descriptive statistics. These tools do not test hypotheses or prove causation; they simply organise and summarise what the data looks like. Understanding them is essential for reading, evaluating, and producing psychological research.
In IB Psychology, descriptive statistics appear most prominently in Paper 3, where you are asked to interpret and evaluate research methodology from a stimulus source. You need to be able to identify which statistics were used, explain what they tell us, and critically assess whether they were the most appropriate choice given the data and research context.
🔍 Analogy — The Weather Report Think of descriptive statistics like a weather forecast. When a meteorologist says "the average temperature this week was 22°C," that single number summarises an entire week of readings. But if one day hit 38°C and another dropped to 6°C, the average alone is misleading. You also need to know how much the temperature varied — the spread. Descriptive statistics work the same way: measures of central tendency (like the mean) tell you the "typical" value, while measures of dispersion (like the standard deviation) tell you how much the data varied around that typical value. Both are needed to understand the full picture.
Core Concepts
Before we can evaluate a psychological study, we need to understand what the researcher's numbers actually mean. Raw data — a list of scores, reaction times, or ratings — is difficult to interpret on its own. Descriptive statistics transform that raw data into summaries that are