CHAPTER 9

Creating Quantitative Data

MANAGEMENT RESEARCH Third Edition, 2008

Prof. M. Easterby-Smith, Prof. R. Thorpe, Prof. Paul R. Jackson

Learning Objectives

To be able to select an appropriate form of sampling design for the objectives of the research.

To be able to select among alternative sources of quantitative data according to the purpose of the research, taking into account the benefits and drawbacks of each.

To be able to design structured questions and select appropriate forms of measurement scale.

Principles in designing a sample

Representativeness: the characteristics of the sample are the same as those of the population from which it is drawn. Biased samples are different from the

population. Precision: credibility of a sample, which depends

on: Sample size – bigger samples are more

precise Sampling proportion – what proportion of

the population is sampled

Achieving a credible sample Bias

High Low

Precision

High a) Precisely right

b) Precisely wrong

Low c) Imprecisely right

d) Imprecisely wrong

Probability Sampling Designs

Simple Random Sampling – every entity has an equal chance of being part of the sample

Stratified Random Sampling – divide the population into strata, and take a random sample from each stratum

Systematic Random Sampling – list the entities in the population, and takes every nth (i.e. 27th) entity

Cluster Sampling – divide the population into clusters and then take samples from each cluster

Multi-Stage Sampling – combines several of the above methods

Non-Probability Sampling Design

Convenience Sampling – selection is based on how easily accessible the sample entities are

Quota Sampling – divide the population into relevant categories and take samples until a target quota is achieved in each category

Purposive Sampling – researcher has a clear idea of what the sample unit should be

Snowball Sampling – use respondents to suggest the names of other relevant respondents to approach

The Value of Sampling Designs

Probability Sampling Designs: the researcher knows the relationship between the sample and the population from which it is drawn

Non-Probability Sampling Designs: the researcher can overcome practical problems, where representativeness of the sample is either unnecessary or impossible to achieve

Sources of Quantitative Data - Surveys

Postal Questionnaires – possible to achieve large samples cheaply

Face-to-face Structured Interviews – costly, but can achieve higher quality data

Telephone Structured Interviews – lower cost, and can achieve higher quality data

Web-based Surveys – can achieve large samples cheaply, easy to customise

Sources of Quantitative Data – Observational Data

Types of observation data: Verbal behaviour – words used to

express meaning Non-Verbal behaviour – vocal & visual

ways of conveying meaning Factors affecting observational data:

Observer effects Sampling & coding behaviour

Sources of Quantitative Data –Secondary Data/Databases

Financial databases – e.g. daily share prices, income statements, mergers & acquisitions

Issues in using secondary data: The structure of the database What data are recorded Forming indices & derived variables

The process of measurement

Principles in designing structured questions

Measurement scales for recording responses

Principles in designing structured questions

Each item should express only one idea

Avoid jargon & colloquialisms Use simple expressions Avoid the use of negatives Avoid leading questions

Measurement scales for recording responses

Category scale Nominal scale – categories have no intrinsic ordering Ordinal Scale – categories have an intrinsic ordering Likert Scale – a type of ordered category scale

Continuous Scale Ratio Scale – has a meaningful zero point Interval Scale – has no meaningful zero point

Further Reading

Gunn (2002) ‘Web-based surveys: changing the survey process’, First Monday, 7 (12).

Couper, M.P., Traugott, M.W. and Lamias, M.J. (2001) ‘Web survey design and administration’, Public Opinion Quarterly, 65 (2): 230-53.

Sapsford, R. (2006) Survey Research, 2nd edn. London: Sage.