At several points in this book, we have returned to the question ‘what is the purpose
of the survey?’ and in deciding on sample size this should again be borne in mind.
Where a high level of accuracy is required from the results, and forecasting or other
generalisations are required from the sample about the rest of the population, then
the size of the sample becomes crucial. However, in more descriptive studies, if 350
people out of 500 interviewed requested extra refreshment facilities at a tourist
attraction, then a management decision might reasonably be based on this alone.
Thus, the need for complicated, predictive statistics requiring large samples may be
unnecessary. Perhaps the first question to ask is the level of accuracy required from
At a second level, the researcher should consider what statistical tests will be
performed on the data. Here again, there is a relationship with the objectives of the
survey. In
Chapter 7
, we will look at analysing results from surveys and this will
show that some statistical tests require a minimum number of responses on which the
test can be satisfactorily executed. If an objective of the survey is to investigate how
age affects the reaction to a product, then the results might be tabulated as seen in
Table 4.3
.
In
Table 4.3
, there are 20 cells (5 columns of opinion scores multiplied by 4 rows
relating to age category). For there to be a possible relationship between age and
opinion to be tested, the sample size needs to be sufficiently large for there to be
responses in each cell. The pilot stage in a survey is useful in showing whether the
classification of categories is appropriate.
A third level of questioning which helps to determine sample size is the amount of
resources the researcher has available. There will be a finite budget in terms of the
time available and the cost of the project. The larger the sample, the greater the
resources required. Larger sizes may therefore result in the need for more staff and
an increased number of survey days for interviews. Hence, sample size is often
influenced by the constraints on the resources available.
At a fourth and final level, the researcher must consider the anticipated response rate
shown by the pilot stage. This is particularly applicable to postal or online surveys. If
the requirements of the survey in terms of the accuracy and statistical analysis call
for 1,000 completed questionnaires and a response rate of 50% are anticipated, then
clearly 2,000 questionnaires would be distributed.
To summarise, to determine sample size in a pragmatic way, the researcher should
consider:
the accuracy required of the results in relation to the objectives of the survey
the requirements of statistical tests in the analysis stage
the available resources for the project
the anticipated response rate.
Illustration 4.7 A sampling excerpt from an undergraduate dissertation
‘Determining the level of consumer-based brand equity (CBBE) in the
airline industry’ by Lauren Polhill, supervised by Andreas Walmsley,
Plymouth University, 2016.
Purpose
The purpose of this study is to provide a framework to determine a level
of consumer-based brand equity (CBBE) in the airline industry, through
assessing brand knowledge amongst consumers and quantifying the
results, in particular drawing on existing studies by Keller (1993), Aaker
(1996) and Yoo and Donthu (2001), and their approaches to measuring
CBBE. Despite CBBE being widely researched, there is no consensus for
quantifying it, which this study aims to do for Emirates, British Airways
and American Airlines.
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