9780273716884 pp07 (1)

1
Saunders, Lewis and Thornhill, Research Methods for Business Students, 5th
Edition, © Mark Saunders, Philip Lewis and Adrian Thornhill 2009
Chapter 7
Selecting Samples

2
Selecting samples
Population, sample and individual cases
Source: Saunders et al. (2009)
Figure 7.1 Population, sample and individual cases

3
The need to sample
Sampling- a valid alternative to a census when
• A survey of the entire population is impracticable
• Budget constraints restrict data collection
• Time constraints restrict data collection
• Results from data collection are needed quickly

4
Overview of sampling techniques
Sampling techniques
Source: Saunders et al. (2009)
Figure 7.2 Sampling techniques

5
Probability sampling
The four stage process
1. Identify sampling frame from research objectives
2. Decide on a suitable sample size
3. Select the appropriate technique and the sample
4. Check that the sample is representative

6
Identifying a suitable sampling frame
Key points to consider
• Problems of using existing databases
• Extent of possible generalisation from the sample
• Validity and reliability
• Avoidance of bias

7
Sample size
Choice of sample size is influenced by
• Confidence needed in the data
• Margin of error that can be tolerated
• Margin of error (also called The confidence interval ) is the plus-or-minus
figure usually reported in newspaper or television opinion poll results. For
example, if you use a margin of error of 4 and 47% percent of your sample
picks an answer you can be "sure" that if you had asked the question of the
entire relevant population between 43% (47-4) and 51% (47+4) would have
picked that answer.
• Types of analyses to be undertaken
• Size of the sample population and distribution

8

9
The importance of response rate
Key considerations
• Non- respondents and analysis of refusals
• Obtaining a representative sample
• Calculating the active response rate
• Estimating response rate and sample size

10
Selecting a sampling technique
Five main techniques used for a probability sample
• Simple random
• Systematic
• Stratified random
• Cluster
• Multi-stage

11
Simple random sampling
• Number each of the cases in your sampling
frame with a unique number.
• Select cases using random numbers until,
actual sample size is reached.
• Computer aided telephone interviewing
(CATI) software

12
Systematic Random Sampling
• Number each of the cases in your sampling frame with a
unique number.
• Select the first case using a random number
• Calculate the sampling fraction
• Select subsequent cases systematically using the
sampling fraction to determine the frequency of
selection.
• Sampling fraction = actual sample size/ total population

13
Stratified random sampling
• Choose the stratification variable or
variables
• Divide the sampling frame into the discrete
strata.
• Number each of the cases within each
stratum with a unique number
• Select your sample using either simple
random or systematic random sampling

14
Cluster sampling
• Choose the cluster grouping for your
sampling frame.
• Number each of the clusters with a unique
number.
• Select sample of clusters using random
sampling

15
Multi-stage sampling

16
Non- probability sampling (1)
Key considerations
• Deciding on a suitable sample size
– Data saturation
• Selecting the appropriate technique

17
Non- probability sampling (2)
Sampling techniques
• Quota sampling (larger populations)
• Purposive sampling
• Snowball sampling
• Self-selection sampling
• Convenience sampling

18
Quota Sampling
• Divide the population into specific groups.
• Calculate quota for each group based on
relevant and available data
• Collect data from each quota

19
Purposive sampling
• Extreme case/deviant sampling: unusual or
special case enable to learn the most about
the RQ.
• Heterogeneous or maximum variation
sampling: representing different subgroups
• Homogeneous sampling: One subgroup.
• Critical case sampling:
– If it happen there, it will happen everywhere.

20
Snowball sampling
• Make contact with one or two cases in the
population.
• Ask these cases to identify further cases.
• Ask these new case to identify further new
cases.
• Stop when either no new cases are given or
the sample is large enough.

21
Self select sampling
• Publicize your need for cases
• Collect data from those who respond

22
Haphazard sampling
• Also called purposive or availability
sampling.
• Select case based on ease or convenience.

23
Summary: Chapter 7
• Choice of sampling techniques depends upon the
research question(s) and their objectives
• Factors affecting sample size include:
- confidence needed in the findings
- accuracy required
- likely categories for analysis

24
Summary: Chapter 7
• Probability sampling requires a sampling frame and
can be more time consuming
• When a sampling frame is not possible, non-
probability sampling is used
• Many research projects use a combination of
sampling techniques

25
Summary: Chapter 7
All choices depend on the ability to gain
access to organisations

9780273716884 pp07 (1)

Recommandé

Recommandé

Contenu connexe

Tendances

Tendances (20)

Similaire à 9780273716884 pp07 (1)

Similaire à 9780273716884 pp07 (1) (20)

Plus de Eaglefly Fly

Plus de Eaglefly Fly (6)

Dernier

Dernier (20)

9780273716884 pp07 (1)