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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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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

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