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Sociological Research MethodsGeneralResearch MethodsOfficial Statistics

AQA GCSE · Question 16 · Sociological Research Methods

University Enrolment by Ethnicity Number of students 0 200 000 400 000 600 000 800 000 1 000 000 1 200 000 1 400 000 1 600 000 Year 2014–15 2016–17 2018–19 Key Ethnicity White Black Asian Mixed/other

SOURCE TEXT:
Item C

The Higher Education Statistics Agency (HESA) produced a report on university enrolment by personal characteristics from 2014/15 to 2018/19. This report found that the vast majority of students that attend university are from white backgrounds, although the number of students from minority ethnic backgrounds is increasing year on year.

[Image of a bar chart showing university enrolment by ethnicity from 2014-15 to 2018-19]

Source: HESA 2020

QUESTION:
From Item C, examine one strength of the research.

How to approach this question

Look at the source of the data (HESA - a government agency). Think about the general strengths of using official statistics in sociological research. Select one strength (e.g., reliability, large scale, trends over time) and explain it in the context of Item C.

Full Answer

One strength of the research is that it is based on official statistics from HESA, which are likely to be highly reliable. Because the data is collected systematically every year using the same categories, another researcher could repeat the exercise and get the same results. This makes the findings trustworthy.
Official statistics, like those from HESA, are a major source of secondary data for sociologists. Their strengths include: they are often collected on a very large scale, making them representative; they are collected regularly over time, allowing for the analysis of trends; they are generally seen as reliable because they are collected in a standardised way; and they are cheap and easy for sociologists to access. However, they also have weaknesses, such as potentially lacking validity if the categories used don't match the sociologist's research aims.

Common mistakes

Stating a strength without linking it to the item. For example, just saying 'it is reliable' without explaining why the data from HESA is likely to be reliable.

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