Slide 7.1 Saunders, Lewis and Thornhill, Research Methods for Business Students, 5 th Edition, ©...

1

Saunders, Lewis and Thornhill, Research Methods for Business Students, 5th Edition, © Mark Saunders, Philip Lewis and Adrian Thornhill 2009

Chapter 7Selecting Samples

2


Selecting samplesPopulation, 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 techniquesSampling 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

Slide 7.1 Saunders, Lewis and Thornhill, Research Methods for Business Students, 5 th Edition, ©...

Documents

Transcript of Slide 7.1 Saunders, Lewis and Thornhill, Research Methods for Business Students, 5 th Edition, ©...