Research Methods Evaluations

Question 1

Experimental Design: Independent Groups

Answer 1

Participant variables are a problem (use random allocation to deal with this).
Less economical than repeated measures as more participants needed.
Order effects are not a problem.
Participants are less likely to guess the aim.

Question 2

Experimental Design: Repeated Measures

Answer 2

Order effects are a problem (counterbalancing is used to deal with this).
Participant variables are not a problem.
Demand characteristics are more likely.

Question 3

Experimental Design: Matched Pairs

Answer 3

Order effects and demand characteristics are less of a problem.
Participant variables are still a problem (but less so than independent groups).
Matching may be time-consuming and expensive so less economical than other designs.

Question 4

Laboratory Experiments

Answer 4

Strengths: high control over extraneous variables, high internal validity, replication is more possible.
Weaknesses: May lack generalisability, artificial stimuli, low external validity, demand characteristics, low mundane realism.

Question 5

Field Experiments

Answer 5

Strengths: higher mundane realism, less demand characteristics, high external validity.
Weaknesses: Loss of control of extraneous variables, cause and effect more difficult to establish, replication is more difficult, important ethical issues.

Question 6

Natural Experiments

Answer 6

Strengths: high external validity, natural setting, provide opportunities for research that may not otherwise be undertaken for practical or ethical reasons, less chance of demand characteristics.
Weaknesses: Difficult to replicate, random allocation for independent groups is difficult, limited generalisability.

Question 7

Quasi-Experiments

Answer 7

Strengths: often carried out under controlled conditions so share strengths of lab.
Weaknesses: cannot randomly allocate participants to conditions and therefore there may be confounding variables.

Question 8

Random Sample

Answer 8

Strengths: free from researcher bias, more representative than some other sample methods.
Weaknesses: difficult and time consuming to conduct, sample may still be unrepresentative, selected participants may refuse to take part.

Question 9

Systematic Sample

Answer 9

Strengths: avoids researcher bias and is usually fairly representative.

Question 10

Stratified Sample

Answer 10

Strengths: avoids researcher bias, representative sample, generalisation of results is possible.
Weaknesses: complete representation of the target population is not possible.

Question 11

Opportunity Sample

Answer 11

Strengths: convenient, more economical.
Weaknesses: researcher bias, unrepresentative of population, not generalisable.

Question 12

Volunteer Sample

Answer 12

Strengths: easy, less time consuming.
Weaknesses: volunteer bias, unrepresentative of population.

Question 13

Naturalistic Observations

Answer 13

Strengths: High external validity and so generalisable.
Weaknesses: Lack of control, replication is difficult, extraneous variables.

Question 14

Controlled Observations

Answer 14

Strengths: extraneous variables are less of a factor, replication is easier.
Weaknesses: results may be less applicable to to real life settings.

Question 15

Covert Observations

Answer 15

Strengths: No participant reactivity, behaviour is natural, increased validity.
Weaknesses: questionable ethics.

Question 16

Overt Observations

Answer 16

Strengths: more ethical
Weaknesses: knowledge of being observed may affect their behaviour and so less valid.

Question 17

Participant Observations

Answer 17

Strengths: researcher has increased insight, potential increased validity.
Weaknesses: researcher may lose objectivity and identify with participants.

Question 18

Non Participant Observation

Answer 18

Strengths: Maintain objectivity.
Weaknesses: May lose valuable insight.

Question 19

Observational Design: Structured Observations

Answer 19

Strengths: Recording of data is easier and more systematic, quantitative data and analysing and comparing is easier.
Weaknesses: Less richness and depth of detail.

Question 20

Observational Design: Unstructured Observations

Answer 20

Strengths: More richness and depth of detail.
Weaknesses: Qualitative data harder to record and analyse, greater risk of observer bias, may only record behaviours that catch the eye.

Question 21

Questionnaires

Answer 21

Strengths: Cost-effective, can gather large amounts of data, usually produce straightforward data that is easy to analyse and compare.
Weaknesses: social desirability bias, response bias, acquiescence bias.

Question 22

Interviews: Structured

Answer 22

Strengths: straightforward to replicate, reduces interviewer differences.
Weaknesses: can’t deviate from topic or elaborate on points.

Question 23

Interviews: Unstructured

Answer 23

Strengths: more flexibility, interviewer more likely to gain insight, interviewer can build rapport with participant.
Weaknesses: Analysis and comparison of data is more difficult, social desirability bias.

Question 24

Peer Review

Answer 24

Strengths: anonymous so more honest appraisal, establishing validity and accuracy of research.
Weaknesses: anonymity can be used to criticise rivals, publication bias, process may suppress opposition to mainstream theories (burying ground breaking theories).

Question 25

Qualitative Data

Answer 25

Strengths: more richness of detail, more license to develop their thoughts, feelings and opinions on a given subject, greater external validity, provides researcher with a more meaningful insight. Weaknesses: difficult to analyse and compare, conclusions often rely on subjective interpretations which may be bias.

Question 26

Quantitative Data

Answer 26

Strengths: easier to analyse and compare, more objective and less open to bias. Weaknesses: less depth and richness of detail, may fail to represent real life.

Question 27

Primary Data

Answer 27

Strengths: authentic data obtained from pps for purpose of the particular investigation. Weaknesses: requires more time and effort.

Question 28

Secondary Data

Answer 28

Strengths: inexpensive and quicker. Weaknesses: may be variation in the quality and accuracy secondary data, may be outdated or incomplete, content may not match researchers needs or objectives.

Question 29

Correlations

Answer 29

Strengths: provide precise and quantifiable measure of relation between variables, quick and economical to carry out. Weaknesses: cannot establish cause and effect, third variable problem.