Research Methods: Final Year Project
Toolkit – Level 6
Laura Lake
The research process
Selecting research
area
Report writing
Formulating
research
questions /
hypotheses
Analysing the
data
Selecting a
research strategy
Collecting data
Research questions
• Research questions – product of theories drawn from:
• literature review
• discussions with professionals or experts
• personal interest
• hunches
The research process
•Deductive – aims to deduce meaning for particular
individuals / cases based on broader principles.
•Can be reductionist –it may break a particular theory or problem
into its many component parts and test each element separately.
•Objective – the phenomenon under investigation must be
observable and verifiable.
• operationalising concepts detailed within hypotheses.
• Inductive: developing theory from findings.
Deductive & inductive
Deductive =
Inductive =
Theory
Observations
/ findings
Observations
/ findings
Theory
Hypotheses
• What is a hypothesis?
• statement or proposal about relationships between
variables of differences between groups that can be
tested.
•Example: is socio-economic group associated with
occupation?
• Used mainly in quantitative rather than qualitative research.
Variables – testing
relationships
• Operationalising concepts – can the hypotheses be
measured and what is the most appropriate way of doing so?
• Example: relationship between age and fear of crime.
• How are the variables ‘age’ and ‘fear of crime’ defined
and how can they be measured?
• A variable is a unit of data collection whose value can vary.
• Cases are individuals (people), organisations,
communities, schools, countries.

Independent variable (x) is a characteristic of the case
under study e.g. sex, age, social class, marital status
Age (x)
Independent)
Income (y)
(Dependent)
Dependent variable (y) is the variable that is causally
influenced by x.
Variables –levels of
measurement
•Variables can be defined into types according to the level of
mathematical scaling that can be carried out on the data.
• There are four types of variable:
1. Nominal
2. Ordinal
3. Interval
4. Ratio
Nominal variables
• Nominal or categorical: variable measured using categories
that cannot be rank ordered.
• No order in categories so no judgement possible about the
relative size or distance from one category to another.
• What does this mean?
•No mathematical operations can be performed on the
variables relative to each other.
• Nominal variables reflect qualitative differences rather
than quantitative ones.
Nominal variables
Examples:
What is your gender?
(please tick)
Did you enjoy the
film? (please tick)
Male
Yes
Female
No
Ordinal variables
• Ordinal : variables that comprises of categories that can be
rank ordered.
• Distance between each category cannot be calculated but
the categories can be ranked above or below each other.
• What does this mean?
• Can make statistical judgements and perform limited
maths.
Ordinal variables
Example:
How satisfied are you with the level of
service you have received? (please tick)
Very satisfied
Somewhat satisfied
Neutral
Somewhat dissatisfied
Very dissatisfied
Interval and ratio
variables
• Both interval and ratio data are examples of scale variables.
• Scale variables:
• numeric format (£50, £100, £150)
•can be measured on a continuous scale
•distance between each can be observed and as a result
measured
•can be placed in rank order.
Interval variables
• Measured on a continuous scale and has no true zero point.
• Examples:
•Time – moves along a continuous measure or seconds,
minutes and so on and is without a zero point of time.
• Temperature – moves along a continuous measure of
degrees and is without a true zero.
Ratio variables
• Measured on a continuous scale and does have a true zero
point.
• Examples:
• Age
• Weight
• Height
Hierarchical variable
order
•These levels of measurement can be placed in hierarchical
order.
Ratio
Interval
Ordinal
Nominal
Hierarchical variable
order
• Example: salary data for is often recorded as interval data
(i.e. just a number).
• Why? Because it can then be analysed in many ways:
• Any mathematical operation e.g. average salary
• reformatted into ordinal or nominal data e.g. salary
bands (£10,000 to £14,999, £15,000 to £19,999)
Hierarchical variable
order
• Salary collected as an ordinal variable i.e. in salary bands?
• Cannot perform mathematical operations e.g. finding
average salary.
• So, if possible capture this kind of data in a scale variable
• This should be thought about at the research design stage!
References
Bryman, A. (2008) Social Research Methods. 3rd Ed. Oxford: Oxford
University Press.
David, M. and Sutton, C. (2011) Social Research : An Introduction.
2nd ed. London: Sage.
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Author
Laura Lake
Research Assistant
Institute
University of Plymouth
Title
Final Year Research Project Toolkit
Description
How to develop research questions and hypotheses
Date Created
July 2011
Educational Level
Undergraduate (Level 6)
UKOER, Learning from WOeRK, LFWOER, UOPCPDRM, Work-Based
Learning, WBL, Continuous Professional Development, CPD, Deductive,
reductionist, objective, inductive, operationalising, variable, nominal,
ordinal, interval and ratio variables.
Keywords
Creative Commons License
©University of Plymouth, 2010, some rights reserved
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