Research Methods Flashcards
(135 cards)
1
Q
What is the Aim in research?
A
This is a general statement describing the purpose of an investigation.
2
Q
What is a hypothesis?
A
It states what you believe to be true. It’s a prediction, a precise and testable statement of the relationship between 2 variables.
3
Q
What is a variable?
A
Anything that can change.
4
Q
What are the 2 variables involved when a hypothesis is operationalised?
A
Independent variable (IV).
Dependent variable (DV).
5
Q
What is the IV?
A
Variable that the researcher manipulates or alters.
6
Q
What is the DV?
A
Measurement taken by the researcher.
7
Q
What affects what? (DV/IV)
A
IV affects DV.
8
Q
What is a operationalised hypothesis?
A
Written in a measurable form, where the variables are precise.
9
Q
What are 2 types of hypothesis?
A
Directional (one-tailed).
Non-directional (two-tailed).
10
Q
Define what’s a one-tailed hypothesis.
A
It states the direction of the predicted difference between 2 conditions or 2 groups of participants.
11
Q
Define what’s a two-tailed hypothesis.
A
It predicts that there will be a difference between 2 conditions or groups of participants, without stating the direction.
12
Q
What is an Extraneous Variable (EV)?
A
Variables that might interfere with the IV/DV that should be controlled or removed.
13
Q
Give some examples of situational EVs.
A
Temperature, noise, lightening, room, time of the day.
14
Q
Give some examples of participants EVs.
A
IQ, caffeine intake generally, sleep, age.
15
Q
What are Confounding variables (CV)?
A
EVs that couldn’t be or weren’t controlled and DID affect the DV.
16
Q
Explain what are Demand Characteristics.
A
Example of an EV.
Clue in the investigation which may help the participant guess the aim of the study.
“Please-U-effect” “Screw-U-effect”
17
Q
What are Investigator effects?
A
Example of a CV.
Cues from an investigator that encourage participants to behave in a particular way; Participants behave in the way that the investigator was expecting.
18
Q
Define what’s Randomisation.
A
Use of chance wherever possible to reduce the influence of the researcher on the design of the investigation. Attempt to control investigator effects.
19
Q
What is Standardisation?
A
When procedures are standardised, all participants are in the same environment, they have the same information and experience…
20
Q
Which 3 things can standardisation include?
A
- Briefing
- Standardised instructions
- Debrief
21
Q
Which are the 3 main ways to allocate participants in an experiment?
A
- Independent measures
- Repeated measures
- Matched pairs
22
Q
Explain what is an independent measures design?
A
It involves using different people in each condition.
23
Q
Give 2 strengths of Independent Measures.
A
- Demand characteristics and order effects are less likely to affect the results.
As each group will have to do 1 condition in the experiment it won’t affect the results. This is because participants won’t have improved their skills in the first condition for the 2nd one.
This adds validity as the results will be more accurate as they aren’t impacted by order effects or demand characteristics. - It’s quicker for a psychologist to complete. Both conditions are done at the same time so the researcher could do different conditions at one time and have a wider set of results, increasing the accuracy.
This adds validity as the results will be more accurate due to larger set of data.
24
Q
What are 2 weaknesses of Independent Measures?
A
- Individual differences are more likely to affect the results. As there are different people in each group, individual differences will affect the DV, such as age, IQ…
This questions the validity as there are other factors that are difficult to control, this can be overcome by RANDOM ALLOCATION. - More participants are needed. RESEARCHESRS will have to invest more money to recruit more participants. This also makes it more time consuming. This questions the validity as it takes more time and money to carry out.
25
Explain what is a Repeated measures design.
It involves using the SAME people in each condition.
26
What are 2 strengths of a Repeated measures design?
- Individual differences are less like to affect the results
| - Psychologists don't need many participants.
27
What are 2 weaknesses of a Repeated measures design?
- There's a higher likelihood of demand characteristics.
Due to there being only 1 group for both conditions, they're more likely to guess the aim of the study as they would have experience in both conditions. This can result to Please-U-effect or the Screw-U-effect.
- It suffers from order effects.
28
What is counterbalancing?
Participants are divided into 2 groups and do the conditions in a different order.
29
Explain what is a Matched pairs design?
It involves using different participants in each condition, but participants are paired with another who is similar in a number of variables.
They're given a pre-test and those with the same score are used and one placed in one condition and the other in the other.
30
What are 2 strengths of a Matched pairs design?
- Individual differences are less likely to affect the results.
- There's a lower likelihood that participants suffer from order effects and demand characteristics.
31
What are 2 weaknesses of a Matched pairs design?
- Very time consuming for a psychologist.
| - It's still impossible to match to people exactly.
32
What are the 2 types of order effects?
Practice and fatigue effects.
33
How can we overcome order effects in a repeated measures design?
By counterbalancing.
34
Define what is target population.
Group of people who the researchers want to apply the results to.
35
Define what is a sample.
Small number of people from the target population who take part in the investigation.
36
How can sampling bias occur?
If the sample selected is not representative of the target population.
37
What can be done to avoid sampling bias?
By selecting a sample as large as possible.
38
What are 5 sampling techniques in psychology?
- Random: everyone has = chance
- Opportunity = people available at the time.... Coffee
- Volunteer...advert
- Systematic = system to select
- Stratified = identify all sub groups from target population
39
Explain 2 strengths of Random sampling.
- There are no researcher bias.
| - It's more likely to be representative.
40
What are 2 weaknesses of random sampling?
- It's very time consuming.
| - It may still not be representative.
41
Explain 1 strength of opportunity sampling.
- It's quicker and easier to do.
42
Explain 2 weaknesses of opportunity sampling.
- Less likely to be representative.
| - There may be researcher bias.
43
What are 2 strengths of Volunteer sampling?
- Quicker and easier to do.
| - There is no researcher bias.
44
What's 1 weakness of Volunteer sampling?
- It's less likely to be representative.
45
What is 1 strength and 1 weakness of Systematic sampling?
- There's no researcher bias.
| - It's less likely to be representative.
46
Explain 2 strengths of Stratified sampling.
- The most representative sampling method.
| - There is no researcher bias.
47
Give 1 weakness of Stratified sampling.
Time consuming and difficult to do.
48
What is a pilot study?
Small scale trial run of the experiment to find out if certain things don't work.
49
What is the ceiling effect?
When tasks are too easy.
50
What is called when tasks are too hard?
Floor effect.
51
Which are the 4 types of experiment?
Lab
Quasi
Field
Natural
52
What are the 5 key features of Lab experiments?
1. Controlled environment
2. Manipulated IV
3. Measurable DV, produces quantitative data
4. Controlled EVs
5. Procedure and instructions are standardised.
53
Explain 2 strengths of Lab experiments.
- High internal validity (controls EVs) as there's a controlled environment.
- High reliability, because it can be replicated easily cause of the standardised procedures.
54
What are 2 weaknesses of Lab experiments?
- Low ecological validity as it's an artificial setting.
| - More likely to suffer from demand characteristics.
55
What are the 5 key features of Quasi experiments?
1. Controlled environment
2. Not manipulated IV, already exists
3. Measurable DV, quantitative data
4. Controlled EVs
5. Standardised procedures and instructions
56
Explain 1 strength and 1 weakness of Quasi experiments.
- High reliability as it can be replicated.
| - Presence of confounding variables.
57
What are the 4 key features of Field experiments?
1. Natural environment
2. Manipulated IV
3. Measured DV, quantitative data
4. Some EVs controlled
58
What are 2 strengths of Field experiments?
- High ecological validity.
| - Fewer demand characteristics.
59
Explain 2 weaknesses of Field experiments.
- Lack of control over EVs.
| - Ethical issues, unaware of study.
60
What are the 4 key features of Natural experiments?
1. Natural environment
2. No controlled IV
3. Measured DVs
4. No control over EVs
61
What are 2 strengths of Natural experiments?
- High ecological validity.
| - Fewer demand characteristics.
62
Explain 2 weaknesses of Natural experiments.
- Lack of control over EVs.
| - Cannot be easily replicated.
63
What is an ethical issue?
Conflicts about what is acceptable.
64
Who proposed ethical issues?
British Psychological Society (BPS)
65
What is Deception and how can you solve it?
It prevents participants being able to give fully informed consent.
By Debriefing, at the end of the research the experimenter should inform participants of the true nature of the study.
66
What's the ethical issue with consent and how can you solve it?
Informed consent is when the researcher informs the participants of the true aims of the study and tells them what's going on.
67
What are some ways of gaining some form of consent?
1. Prior general consent
2. Presumptive consent
3. Parental consent
68
How can we solve the ethical issue of protection of participants and what is it?
By Protection from harm, to test whether they suffered more than they would in their everyday life.
Psychological or physical harm.
69
What is right to withdraw and how can we solve it?
If participants begin to feel uncomfortable or distressed they should be able to withdraw.
Right to withdraw, participants should be informed at the beginning of the investigation about it.
70
What's the ethical issue of confidentiality and how can we solve it?
Participants have the right to control information about themselves.
Anonymity must be maintained.
71
What's the ethical issue of privacy and how can we solve it?
Participants have the right to control information about themselves.
Participants should not be studied in certain situations where they wouldn't expect to be normally seen.
72
What is Reliability?
Extent to which the results are consistent. Therefore, whether the researcher can repeat the study and get the same results.
73
What are the ways of assessing reliability?
1. Inter-observer reliability
| 2. Test re-test reliability
74
How can you assess reliability using inter-observer reliability?
-Extent to which 2 observers give consistent scores or estimates of behaviour.
75
How can you improve inter-observer reliability?
1. Training: give better training.
2. Operationalisation: both are clear on what they're looking for + use categories of behaviour grid.
3. View of behaviour: both have same view.
76
How can you assess reliability using test-retest reliability?
Extent to which a tool is consistent or stable over time.
77
How can you improve test-retest reliability?
Alter the test: looking closely and identifying the parts that didn't correlate well on 2 occasions and removing them.
78
What is validity?
Extent to which the tool MEASURES what it's supposed to measure.
79
What are 3 types of validity?
Internal
External
Temporal
80
What is internal validity?
Extent to which we can say the test measures what it's supposed to measure and the findings are due to the IV only.
81
How can you improve the internal validity.
- Minimising EVs
- Careful planning + careful choice of research design
- Use a lab experiment
- Matched pairs
- Stratified sampling
- Standardised procedures
- Independent measures
82
What is external validity? What 2 types are there?
Extent to which the findings can be generalised.
- Ecological: How true to real life
- Population: How true to the population sample
83
How can you improve external validity?
Ecological:
- Field or natural experiment
- Use deception then debrief at the end
- Create more realistic task + independent groups
Population:
- Stratified sampling
- Random sampling
- Large sample
84
What is temporal validity?
Extent to which the findings of a study are relevant in today's society.
85
In which 2 ways can you assess validity?
1. Concurrent validity
| 2. Face validity
86
What is quantitative data?
Numerical data that involves measuring something.
Statistical analysis can be used and is collected in experiment-based research methods.
Closed questions.
87
What is qualitative data?
Non-numerical data that involves finding out what people think and how they feel.
Qualitative analysis can be used and is collected in case studies, unstructured observations/interview.
88
What are 1 strength and 1 weakness of quantitative data?
- Less subjective
| - Limits the amount of research you can find.
89
What are 1 strength and 1 weakness of qualitative data?
- Gives more detailed and in-depth data.
| - More difficult and time consuming to analyse.
90
Explain what is primary data.
Original data collected specifically towards a research aim, which has NOT been published before.
91
Explain what is secondary data.
Data collected towards another research aim, which has been published before.
92
What are 1 strength and 1 weakness of primary data?
- Reliable, more valid.
| - Very expensive and time consuming to conduct.
93
What are 1 strength and 1 weakness of secondary data?
- Cheaper and quicker to use.
| - Less valid, might not fit the needs of the hypothesis exactly.
94
Define Sign Test.
Used to determine whether something is significant or not.
95
What is the criteria for using a sign test?
- Look for a difference
- Use a repeated measures design
- Nominal data (categories)
96
What does N represent in a sign test?
Number of participants
97
How should you report the results of a sign test?
Since the calculated S value is less than the critical table value, the null hypothesis can be rejected. It was found that ............... (S=....,N=....,p ≤ 0.05, -tailed)
98
What are descriptive statics used for?
They allow us describe and summarise quantitative data.
99
What are the 2 types of descriptive statics?
- Measures of central tendency.
| - Measures of dispersion.
100
What's a measure of central tendency?
It reduces a large amount of data to a single value which is representative of that set of data.
101
Which are the 3 measures of central tendency?
1. Mean: statistical average
2. Median: central value
3. Mode: most frequently occurring score
102
Give 1 advantage and 1 disadvantage of the Mean.
- Uses all scores, most representative.
| - Can be distorted by extreme scores making it unrepresentative. These scores are anomalies/outliers.
103
Give 2 advantages and 1 disadvantage of the Median.
- Unaffected by extreme values.
- Easier to calculate than the mean.
- It only takes into account one or two scores.
104
Give 2 advantages and 2 disadvantages of the Mode.
- Unaffected by extreme values.
- Easier to calculate than the mean.
- Not useful in small sets of data.
- It doesn't take into account the other scores.
105
What are measures of dispersion?
This includes:
- Range - taking away the lowest score from the highest.
- Standard deviation - More precise method, spread of data around the mean.
106
What is a null hypothesis?
Opposite to a hypothesis as it predicts that the IV won't affect the DV, there will be no difference between the conditions.
107
Define experimental hypothesis.
It says the IV will affect the DV (directional/ non-directional).
108
What is a type 1 error?
False positive. Accepts the experimental hypothesis and rejects the null hypothesis when they shouldn't as the result was due to chance.
109
What is a type 2 error?
False negative. Rejects the experimental hypothesis and accepts the null hypothesis when they shouldn't as the results weren't due to chance.
110
Define what's nominal level data.
Data in categories.
111
Which data is ordinal level data?
Data is in an order/rank.
112
What is interval level data?
Most accurate form. Measuring something in a scale.
113
What 3 questions should you do to choose a statistical test?
| Learn table
1. Level of measurement?
2. Correlation looking for a relationship? Or looking for difference?
3. Experimental design?
114
What does a consent form need to include?
- Purpose of the investigation
- Procedural information
- Ethical information
115
What does procedural information include?
- Way in which participants' functioning will be assessed before and after "treatment".
- Researcher is trained.
- Duration of procedure.
- Random allocation of participants to conditions.
116
What does ethical information include?
- No pressure of consent.
- They can withdraw at any time.
- They can withdraw their data from study.
- Their data will be kept confidential + anonymous.
- Feel free to ask.
117
Which should be the structure of a report?
```
Title
Abstract
Introduction
Method
Results
Discussion
References
Appendix
```
118
What does replicability involve?
Being able to repeat the study to see if you can get the same results.
119
What is a theory?
Collection of general principles that explain facts and observations, these help us predict and understand the phenomena around us.
120
What is hypothesis testing for?
To modify theories.
121
What do empirical methods involve?
Using a method where you can physically see and measure the outcome.
122
What is a paradigm?
A shared set of assumptions and methods about a subject.
123
Define what's a peer review.
Process that takes place before a study is published to check the quality and validity of the research, and to ensure that the research contributes to its field. The process is carried out by experts in that particular field of psychology.
124
Define Natural Observations.
It involves studying the spontaneous behaviour of participants in natural surroundings. The researcher simply records what they see in whatever way they can.
125
Evaluate Natural Observations.
| 1 strength + 1 limitation
+ High ecological validity.
| - Cannot be replicated to check reliability, as the researcher is not in control of variables.
126
Define Controlled Observations.
The researcher decides where the observation will take place, at what time, with which participants, in what circumstances and uses a standardised procedure.
127
Evaluate Controlled Observations.
| 1 strength + 1 limitation
- Low ecological validity, artificial environment.
| + Can be replicated to check reliability.
128
Define Covert Observations.
Involve the researcher not informing members of the group the reason for their presence.
129
Evaluate Covert Observations.
| 1 strength + 1 limitation
+ Investigator effects are unlikely meaning that participants’ behaviour will be natural.
- Less ethical as participants are not aware they are taking part and cannot give fully informed consent.
130
Define Overt Observations.
Refer to the researcher being open about their intentions in the field and ensuring all members of the social group are aware of what is happening.
131
Evaluate Overt Observations.
| 1 strength + 1 limitation
+ It is possible to inform participants in advance and obtain informed consent.
- Behaviour can be distorted through investigator effects.
132
Define Participant Observation.
Involves observing participants actively participating with them.
133
Evaluate Participant Observation.
| 1 strength + 1 limitation
+ The researcher can obtain in-depth data.
| - The researchers’ presence might influence the participants’ behaviour.
134
Define Non-participant Observation.
Involves observing participants without actively participating.
135
Evaluate Non-participant Observation.
| 1 strength + 1 limitation
+ Investigator effects are less likely to happen.
| - Due to a lack of proximity the researcher might overlook or miss behaviours of interest.
