Introduction To Quantitative Research

Question 1

Why do quantitative research?

Answer 1

To investigate human behaviour using numerical data
To test a hypothesis
To test cause and effect relationships
Generate causal laws, which are generalisable

Question 2

What is the quantitative approach to research?

Answer 2

Associated with a positivist approach
Natural, objective reality exists and can be measured
Reality is independent of social context
Focus on prediction and hypothesis testing
Deductive reasoning

Question 3

Quantitive approach to research continued:

Answer 3

Makes causal statements
Values reliability, generalisability
Sources of error in observation viewed negatively
Researcher is independent and without bias

Question 4

What do you include when writing quantitative research questions?

Answer 4

Make causal statements
Make predictions
State hypothesis

Question 5

What does quantitative research include?

Answer 5

Hypothetico-deductive method
Observation and data collection
Development of explanatory theory
Development of hypothesis (deductive)
Test of hypothesis (research prediction)
Conclusion: evidence support or challenges theory

Question 6

What methods do quantitative studies use?

Answer 6

Empiricism - observation, measurement, and numerical results

Methods of data collection - questionnaire survey, experiments, quasi-experiment

Question 7

What experimental design structure do quantitative studies use?

Answer 7

Aim: to isolate cause and effect and eliminate alternative explanations for observed relationships
Method: manipulation of the IV to observe effect on the DV whilst controlling extraneous and confounding variables e.g. Randomisation

Question 8

What are the different types of experimental designs?

Answer 8

True experiment

Quasi-experiment

Question 9

What are some examples of questionnaire surveys?

Answer 9

Eurobarometer
European social survey
World values survey
World database of happiness

Question 10

What is the different between experimental study designs and correlational study designs?

Answer 10

Experimental manipulate variables to enable researchers to identify cause and effect relationships

Correlational measure but do not manipulate variables and cannot identify cause and effect relationships

Question 11

What are key concepts of quantitative research?

Answer 11

Samples, populations
Constructs, variables, operational definitions
Levels of measurement
Reliability and validity

Question 12

What is a sample?

Answer 12

People you are actually collecting data from

Question 13

What is a population?

Answer 13

A wider group you are trying to generalise your results to

Question 14

What is important about samples and populations?

Answer 14

Your sample needs to be representative of your population of interest

Question 15

What is external validity?

Answer 15

Can you generalise from your sample (specific time, people, place) to your population of research interest

Question 16

What is a problem of external validity?

Answer 16

Non-representative samples

Question 17

How do you choose a sample?

Answer 17

Random probability sample
Random with stratification
Convenience (non random)
Snowballing
Critical cases

Question 18

What is a construct?

Answer 18

A broad concept of research interest

Concept we are interested in

Question 19

What is a variable?

Answer 19

The thing that varies (usually a score)

Score on our measure

Question 20

What is the definition of operational?

Answer 20

A valid method for measuring the construct of interest: often a test

(Measure or test used)

Question 21

What are some lists of measurement?

Answer 21

Nominal/categorical
Ordinal
Interval
Ratio

Question 22

What are the levels of nominal and ordinal measurement?

Answer 22

Nominal/categorical: numbers are only labels for categories e.g. Female: 1 Male: 2

Ordinal: numbers are labels for categories and these categories can be ordered e.g. Positions in a running race

Question 23

What are different levels of measurement?

Answer 23

Interval: each unit on a scale represents an equal change in the variable measured e.g. Height measured in cm

Ratio: interval scale with a meaningful absolute zero e.g. Temperature measured in Fahrenheit

Question 24

What is reliability?

Answer 24

Talking about the consistency of measurement

Question 25

What is validity?

Answer 25

Does this test measure what it claims to?

Question 26

What are the different ways to describe your data?

Answer 26

Mean - the average
Median - the middle number when ordered
Mode - the most common number

Question 27

How does my data vary?

Answer 27

Standard deviation

Variance

Question 28

What are the strengths of quantitative research?

Answer 28

Large samples, extrapolation to populations of interest
Can make claims to reliability and validity
Able to make and test predictions
Objective measurement of behaviour

Question 29

What are limitations of quantitative research?

Answer 29

Loses complexity of real life; variability is ‘error’
Neglects ‘whole person’
Difficult to investigate things that can’t be easily measured
Ignores function of talk, ignores of meaning changes with context

Question 30

What makes good quantitative research?

Answer 30

Reliability and validity of the measures used
Internal validity - particularly for experimental designs
External validity and generalisability
Extent to which study method and findings are replicable

Question 31

What is the key criteria for evaluating quality in experimental research?

Answer 31

Is there a control group?
Are the groups randomly assigned?
Is the control group given an alternative treatment?
Outcome measure; reliability, validity, multidimensional
What causes drop out?
What are the exclusion criteria?