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EnglandPsychologySyllabus dot point

How do psychologists summarise and present quantitative data using measures of central tendency, dispersion and graphs?

Descriptive statistics: measures of central tendency (mean, median, mode), measures of dispersion (range, standard deviation), levels of measurement (nominal, ordinal, interval), percentages and ratios, and presenting data (tables, bar charts, histograms, scattergrams).

An Eduqas A-Level Psychology answer to descriptive statistics in Component 2. Covers the mean, median and mode, range and standard deviation, levels of measurement, percentages and ratios, and how to present quantitative data in tables, bar charts, histograms and scattergrams, with worked calculations.

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  1. What this dot point is asking
  2. The answer
  3. Examples in context
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What this dot point is asking

Component 2 requires you to summarise and present quantitative data. You must know the measures of central tendency and dispersion, the levels of measurement, percentages and ratios, and how to choose and draw the right graph, including doing calculations.

The answer

Central tendency

Dispersion

Levels of measurement and presenting data

  • Nominal (categories, for example eye colour), ordinal (ordered ranks, for example a rating scale), interval (equal units, for example reaction time). The level determines the appropriate average and statistical test.
  • Percentages and ratios express proportions, for example 1560=25%\frac{15}{60} = 25\%.
  • Tables summarise; bar charts show discrete categories (gaps between bars); histograms show continuous data (no gaps); scattergrams show correlations.

Examples in context

Example 1. Why the mean can mislead. In the set 2, 3, 3, 4, 88, the mean (2020) is dragged up by the outlier 8888, while the median (33) better represents the typical value. This shows why the median is preferred for skewed data with outliers.

Example 2. Standard deviation and consistency. Two classes can share a mean of 60%60\%, but if one has an SD of 55 and the other an SD of 2020, the first class is far more consistent. Reporting the SD alongside the mean reveals this difference, which the mean alone hides.

Try this

Q1. Calculate the mean of 5, 7, 9, 9, 10. [2 marks]

  • Cue. Sum =40= 40, n=5n = 5, mean =40/5=8= 40 / 5 = 8.

Q2. State which measure of central tendency is suitable for nominal data and why. [2 marks]

  • Cue. The mode, because nominal data are categories with no order or numerical value, so only the most frequent category can be identified.

Q3. Explain what a large standard deviation tells you about a data set. [2 marks]

  • Cue. That the scores are widely spread out from the mean (the data are inconsistent or varied), rather than clustered close to the mean.

Exam-style practice questions

Practice questions written in the style of WJEC Eduqas exam questions on this dot point, with worked answer explainers. The year tag is the paper they imitate, not the source.

Eduqas 20196 marksFor the data set 4, 6, 6, 8, 11, calculate the mean, the median and the mode. [6 marks]
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A calculation item (AO2). Maths content.

Mean: add the values and divide by the number of values. Sum =4+6+6+8+11=35= 4 + 6 + 6 + 8 + 11 = 35; there are 5 values, so the mean =35/5=7= 35 / 5 = 7.

Median: order the data (already ordered: 4, 6, 6, 8, 11) and take the middle value. With 5 values the middle is the 3rd, so the median =6= 6.

Mode: the most frequent value. 6 appears twice, all others once, so the mode =6= 6.

Markers reward the correct method and answer for each: mean 77, median 66, mode 66.

Eduqas 20216 marksExplain why the standard deviation is often a more informative measure of dispersion than the range. [6 marks]
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A knowledge item (AO1/AO3). Maths content.

The range is the difference between the highest and lowest values (range=highest−lowest\text{range} = \text{highest} - \text{lowest}). It is quick to calculate but uses only the two extreme scores, so it is distorted by a single outlier and ignores how the rest of the data are distributed.

The standard deviation measures the average distance of all scores from the mean, so it uses every value and gives a fuller picture of the spread. A small standard deviation means scores cluster near the mean (consistent data); a large one means they are widely spread. It is more sensitive but assumes interval data and a roughly normal distribution.

Markers reward the contrast: the range uses only two values and is outlier-sensitive, while the standard deviation uses all values and describes the spread more precisely.

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