Chapter 1
Statistics and Research Design
In everyday use the word statistics has two meanings. In one sense it refers to the way we
collect, analyze and interpret numerical facts which are termed data. Second, statistics
are in themselves the raw numerical data resulting from observations or measurements, or
are the results of calculations derived from such data. The term statistical analysis is
often used and in general this may refer to the descriptive use of statistics to present and
summarize data, or it may mean the way in which these statistics are used to make
statistical inferences. This is the process whereby statistical information obtained from a
sample is used to draw conclusions which have wider applicability than solely to the
sample of observations or measurements obtained and is referred to as the inferential use
of statistics.
Statistical inferences are described in terms of probability; the likelihood or chance in
the long-run of occurrence of an event. In statistical jargon an event means any
outcome(s) from among a set of all possible outcomes. The concept of probability is used
in statistical modelling which compares patterns of variability and frequency of
outcomes in real data with the idealized frequency of outcomes that would be expected
from a statistical probability model. We can think of such a probability model as a
mathematical representation to describe and predict phenomena such as patterns and
relationships in data and outcomes of experiments. Interpretation of the fit or match of
data to a particular statistical model can provide insight into the phenomena being
investigated.
Data, however, do not interpret themselves and may be meaningless unless descriptive
statistics are used to arrange numbers into a coherent and more meaningful summary of
information. Inferential statistical techniques are the tools which can then be used to
analyze data, answer specific questions, draw trustworthy conclusions and thereby gain
information which might not be apparent from an initial scrutiny of data.
In this chapter we begin by emphasizing the importance of statistical thinking in
research design and then go on to examine the role which statistics plays in the planning
and data collection stages of a study. Next, we review the general principles and
distinguishing features of survey and experimental designs and then present statistical
guidelines which can be referred to during the design stage of a study or which can be
used in the assessment of research papers, reports and manuscripts.