Research methods Flashcards
1
Q
What is an Independant Variable?
A
Some event that is directly manipulated by experimenter in order to test its effect on the DV.
2
Q
What is a Dependant Variable?
A
A measurable outcome of the action of the independent variable in an experiment.
3
Q
What is an extraneous Variable?
A
Variables which may effect the dependant variable but do not act as an independent variable. Nuisance variables that muddy the waters and make it more difficult to detect a significant effect.
4
Q
What is Mundane realism?
A
How an experiment mirrors the real world. ‘Mundane’ means ‘of the real world’ - commonplace, ordinary.
5
Q
What does Control mean?
A
Refers to the extent which any variable is held constant or regulated by a researcher.
6
Q
What is External validity?
A
The degree to which a research finding can be generalised: to other settings (ecological validity); other people (population validity); over time (temporal/historical validity).
7
Q
What is internal validity?
A
The degree which an observed effect was due to the experimental manipulation rather than other factors such as confounding/extraneous variables.
8
Q
What does Validity mean?
A
Refers to whether an observed effect is a genuine one.
9
Q
What is a confounding variable?
A
A variable under study that is not the IV but which varies systematically with the IV.
10
Q
What does confound mean?
A
To cause confusion.
11
Q
What is a laboratory experiment?
A
An experiment conducted in a special enviroment where variable can be carefully controlled.
12
Q
What is a field experiment?
A
An experiment conducted in a more natural enviroment i.e. in ‘the field’.
13
Q
What are strengths of Laboratory experiements?
A
- Usually high in internal validty because extraneous variables can be controlled.
14
Q
What are limitations of Laboratory experiements?
A
- Participants usually are aware that their behaviour is being studied. Leading to particpants searching for cues about the aims of the experiments and affect behaviour reducing realness.
- The IV and DV may be operationalised in such a way that it doesn’t represent everyday experiences, i.e low in mundance realism.
- Low ecological validty can also be explained in terms of setting. Participants may feel uncomfortable in an unknown and artifical enviroment. Causes change in usual behaviour.
- Materials may lack mundane realism.
15
Q
What are strengths of Field experiments?
A
- Participants are not likely to be aware that their behvaiour is being studied
- A field experiment takes places in a more natural setting (e.g a classroom), particpants are more relaxed.
16
Q
What are limitations of Field experiments?
A
- It is more difficult to control extraneous variables.
- There is a major ethical issue
17
Q
What is a Natural Experiment?
A
An experiment conducted when it is not possible, for ethical or practical reasons, to deliberately manipulate an IV.
18
Q
What are the strengths of Natural experiments?
A
- Allows research where IV can’t be manipulated for ethical or practical reasons.
- Enables researchers to study ‘real’ problems such as the effect of a disaster on health (increased mundane realism and ecological validty).
19
Q
What are limitations of Natural experiments?
A
- Cannot demomstrate causal relationships because IV not directly manipulated.
- Can only be used where conditions vary naturally.
- Participants may be aware of being studied, creating demand characteristics and reducing internal validity.
- The DV may be a fairly artficial task, reducing mundane realism.
20
Q
What is strength of Quasi-experiments?
A
Allows comparisons between types of people.
21
Q
What are limitations of Quasi-experiments?
A
- Participants may be aware of being studied, creating demand characteristics and reducing internal validty.
- The DV may be a fairly artificial task, reducing mundane realism.
22
Q
Operationalise
A
Ensuring that variables are in a form that can be easily tested. E.g a GCSE maths grade.
23
Q
Hypothesis
A
A precise and testable statement which is based on an assumption of a relationship between variables.
24
Q
Aim
A
An statement of what the reseacher intend to find out in a research study.
25
What is an experiment?
A research method where causal conclusions can be drawn because an IV has been deliberatley manipulated to observe the casual effect on the DV.
26
What are Standardised procedures?
A set of procedures that are the same for all p's in order to be able to repeat the study.
27
Debriefing
A post-research interview designed to inform participants of the true nature of the study and to restore them to the state they were in a the start of the study.
28
What is Counterbalancing?
An experimental technique usted to overcome order effects when using a repeated measures design.
29
What is a Experimental design
A set of procedures used to control the influence of factors as p's variables in an experiment.
30
What is an independent groups design?
P's are allocated to two (or more) groups representing different levels of IV. Allocation is usually done using random techiniques.
31
Matched pairs design
Pairs of p's are matched in terms of key variabls such as age and IQ.
32
Random allocation
Allocating participants to experimental groups or conditons using random techniques.
33
Repeated measure design
Each p's takes part in every conditon under test, I.e each level of the IV.
34
Order effect
In a repeated measure design an extraneous variable arising from the order in which conditions are presented. Eg fatigue effect
35
What are the strengths of Mean?
Most sensitive measure of central tendency as it includes all the raw data most suitable for interval or ratio data.
36
What are the limitations of Mean?
Can be biased by skewed (outlying) scores often means score is not one of the original scores (eg. 2.4).
Can not be representative of the data at all times eg average family size 2.4 children!
37
What is the strengths of Median?
- Not affected by extreme scores.
- Most appropriate for ordinal data
- quick and easy to calculate
- Can be more representative on a set of skewed scores
38
What is the limitations of Median?
- Not as sensitive as the mean.
| - Not used in further statistical calculations
39
What are the strengths of Mode?
- Not affected by the extreme scores
| - Can make more sense eg. average number of children in a family is 2 (mode) rather than 2.4
40
What is the limitations of Mode?
- Not v. useful if more than one modal score.
| - Tells us nothing about the other scores
41
What is the definition of Case studies?
Detailed study of a single individual/small group by using a self-report and/or observational techniques.
42
Ethical issues
Concern questions of right or wrong. They arise in research where there are conflicting sets of values between researchers and p's concerning the goals, procedure or outcomes of a research study.
43
What are the ethical issues for a laboratory experiment?
If deception used - would need to gain consent from the ethics committee or presumptive consent.
44
What are the ethical issues for a Quasi-experiment?
-
45
What are the ethical issues for a Natural experiment?
- Consent
- Invasion of privacy
- Deception
46
Give an example of a Natural experiment
Kiecolt- Glaser - Measuring stress and immune system response - Took blood samples one month before medical final exams. (Low-stress condition) and on the first day of final exams (High).
Researcher did not create change in stress
47
Give an example of a Laboratory experiment
Loftus and palmer - Manipulated the word used in the lab experiment asking p's to estimate the speeds cars were driving having seen a short video of a car collision.
48
Give an example of a Quasi-experiment?
Sheridan and King (1972) tested obedience by asking male p’s to give genuine electric shocks of increasing strengths to a puppy. 54% of males delivered maximum (deadly) shock but the obedience rate of females was 100%.
49
Give an example of a Field experiment?
Ceci & Bruck - Sam stone experiment. The researcher manipulated the IV but the experiment was in the P's natural setting - Classroom
50
Inter-observer reliability
The extent to which there is an agreement between two or more observers involved in observations of behaviour
51
Naturalistic observation
Observing spontaneously occurring behaviour in the participant’s own natural environment:
52
Controlled observations
- Occurs when the researchers control some variables
| - Can occur in a laboratory or natural situations
53
Unstructured observations
Researchers record the behaviour they can see.
54
Advantages of Unstructured observations
provides a great deal of rich, qualitative data
55
Disadvantages of Unstructured observations
- can be difficult to analyse the tendency for observers to
| notice the most eye-catching behaviours that may not be most relevant
56
Structured observations
- Design a type of coding system to record participants’ behaviour
- Often made to record how often a type of behaviour appears
57
Advantages of Structured observations
- Simple to carry out
| - Quantative data which can be statistically analysed
58
Disadvantages of Structured observations
- Gives a very redistributed view of which is happening
| - Researcher may miss important behaviour
59
What at the two observational sampling methods for Structured observations?
Event sampling
Time sampling
60
Event sampling
Taking count of each time a particular behaviour occurs (as in the behaviour checklist)
61
Time sampling
Recording observations at specific time intervals- eg recording behaviours every 30 seconds
62
Self-report techniques
The participants report their beliefs, attitudes and experiences to a researcher
63
What are the types of Self-report techniques?
Questionnaires - open & closed
Interviews - Structured, unstructured & Semi-structured
64
What are the advantages of Questionnaires?
- Quick and cheap
- Large samples
- Gain Qualitative and Quantitive date
- Easy to Replicate
65
What are the weaknesses of Questionnaires?
- Misunderstanding (leading questions/wording)
- Biased samples
- Social desirability (p’s may present in a positive light.
66
What are the types of Observations techniques?
Naturalistic/Controlled
Overt/Covert
Participant/Non-participant
67
Correlation
A method used to analyse data not a research method
68
What is a correlation used for?
Analyse the association between two variables, in this case co-variables
69
Strengths of Correlational Analysis
- Can be used when it would be unethical or impractical to manipulate variables
- Justifies further research. - If correlation is significant may justify further research, if not significant canrule out any casual relationship
70
Weaknesses of Correlational Analysis
- cannot establish cause and effect - Only relationship between co-variables
- May lack internal and external validity - method used to measure IQ may lack internal validity or the sample used may lack generalisability
71
Directional hypothesis (one/tail)
States the direction of the predicted different (or relationship in the correlational study) between two condition or two groups of participants.
72
Non-directional hypothesis (two/tailed)
Predicts that their is a difference (or relationship in correlational study) between two conditions or two groups of participants but doesn’t state the direction.
73
Null hypothesis
This predicts that a statistically significant effect or relationship will not be found.
74
Meta analysis
A research looks at findings from a number of different studies and produced a statistic to represent the overall effect.
75
Effect size
A measure of strength of the relationship between two variables
76
Strengths of meta analysis
- Increase validity of the conclusions drawn as they are based on a wider sample of participants.
- Allows us to reach an overall conclusion by having statistic to represent the findings of different studies
77
Limitations of Meta analysis
- The studies are not truly comparable. - Conclusion may not all be valid
78
Content analysis
A observational study in which behaviour is observed indirectly in written or verbal material eg interviews, conversations, books, diaries or TV shows
79
Strengths of Content Analysis
- Based on observations - real communication ma that are current and relevant eg recent newspapers. High ecological validity
- When sources can be retained or accessed by others eg back copies of magazines or videos of people. Finding can be replicated
80
Limitations Content analysis
- Observer his reduced the objectivity and validity findings as different observers may interpret the meaning of behavioural categories differently.
Lack reliability and internal validity
81
Case study
A research investigation that involves a detailed study of a single individual, institution or event.
82
Strengths of a case study
- Provides rich, in-depth data, so informs that may be overlooked using other methods is likely to be identified.
- useful to investigate instances of human behaviour and experience that are rare eg cases of people with brain damage responding to event such a london riots
- Complex interaction of many factors can be studies in contrast with experiments where many variables are help constant
83
Limitations of Case studies
- difficult to generalise from individuals cases as each 1 has unique characteristics.
- More ethical issues such as confidentiality
- it is often necessary to use recollection of past events of the case history and may be unreliable.
- Researchers may lack objectivity as they get to know that case, or as theoretical bias may lead to them to overlook aspects of findings
84
Strengths of mean
Most sensitive measure of central tendency includes all the raw data. Most suitable for interval or ratio state
85
Limitations of Mean
- Can be biased by skewed (overlying) scores.
- often mean score is not one of the original scores (2.4)
- Can not be very representative of the data at times eg average family is 2.4 children
86
Strengths of median
- not affected by extreme scores
- Appropriate for ordinal (ranked) data
- it can be wiser to calculate the mean
87
Limitations of Median
- Not as sensitive as the mean as the exact values are not reflected in the final calculation
- Not used in further statistics calculations
88
Strengths of Mode
- Unaffected by extreme values
- It is much more useful for discrete data.
- The only method that can be used when data is in categories i.e nominal data
89
Limitations of Mode
- Not a useful way of describing stats when there are several modes
- It also tells us nothing about the other values in a distribution
90
Range
The difference between the highest and length west item in a date set. Usually 1 is added as a correction
91
Strengths are of range
East to calculate
92
Limitations of range
- affected by extreme values
- Fails to take account the distribution of numbers eg does not indicated whether number are closely groups around the mean or spread out evenly
93
Standard deviation
The amount of variation in a data set. It assesses the spread of data around the mean
94
Strengths of SD
- is a precise measure of dispersion as it takes all the exact values into account
- Not difficult to calculate if you have a calculator
95
Limitations of SD
- May hide some characteristics of the date set eg extreme values
96
Primary data
Information observer or collected directly from firsthand experience
97
Secondary data
Information used in a research study that was collected by someone else or for a purpose other than the current one eg published data or data collected in the past
98
Strengths of primary data
Researcher has control over the data. Data collection can be designed so it fits the aims and hypothesis of the study.
99
Limitations of primary data
Lengthy and expensive process
100
Strengths of secondary data
Simpler and cheaper to access someone else’s data
101
Limitations of secondary data
For some studies, the data may not exactly fit the need of the study.
102
Collection techniques for primary data
Data collected by the researcher of the current study through any research method e.g. questionnaire observation experiment
103
Collection techniques for secondary data
E.g. governments to sticks data held by the hospital or other institution
104
Longnitutnial studies
