Research Methods Flashcards

1
Q

Features of Science

A

Objectivity
Repeatability
Measurable and testable concepts
Trial and error
Hypothesis testing
Paradigm shifts

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2
Q

Aim

A

A general expression of what the researcher intends to investigate

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3
Q

Hypothesis

A

A predictive statement of what the research believes they will find
Directional (one tailed) - states whether changes will be greater or lesser
Non-directional (two tailed) - predicts difference / correlation

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4
Q

Independent Variable

A

The thing you change to see the effect on the DV

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5
Q

Dependent Variable

A

The thing you are measuring

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6
Q

Extraneous Variables

A

Other things that could affect the DV that you are not measuring

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7
Q

Confounding Variable

A

Other variable that have affected your results

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8
Q

Demand Characteristics

A

Any cue from the research situation or researcher that may reveal the aim of the the study and ptps react accordingly
= research issue

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9
Q

Pilot Study

A

A trial run of the research to work out any problems

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10
Q

Randomisation

A

The use of chance when designing an investigation to control for the effects of bias
= research techniques

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11
Q

Standardisation

A

Using exactly the same formalised procedure for all ptps in the same study
= research technique

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12
Q

Control Groups

A

Used for the purpose of setting a comparison
Act as a baseline to help establish causation

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13
Q

Single Blind

A

Ptp doesn’t know the aim of the study

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14
Q

Double Blind

A

Ptp and researcher don’t know the aim of the study

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15
Q

Independent Groups

A

One group condition A and the second group to condition B
Ptps should be randomly allocated to groups
No order effects
Less likely to guess aim
Ptp variables
More ptps used

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16
Q

Repeated Measures

A

Same ptps in all conditions
The order should be counterbalanced to avoid order effects
Ptps variables
Fewer ptps
Order effects
Ptps may guess aim

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17
Q

Matched Pairs

A

Two groups of ptps are used but are related to each other by being paired in Ptp variables that matter to the experiment
Ptp variables = matched
No order effects
Matching not perfect
More ptps

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18
Q

Lab Experiment

A

Controlled environment when EVs and CVs can be regulated
Ptps go to researcher
IV = manipulated and the effect on the DV recorded

EVs & CVs = controlled
Can be easily replicated
May lack gen
DCs

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19
Q

Field Experiment

A

Natural setting
Researcher goes to ptps
IV = manipulated and effect on DV = recorded

More natural environment
Greater external validity
More difficult to control CVs
Ethical issues

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20
Q

Natural experiment

A

Doesn’t manipulate IV - would have varied even if the experimenter not interested
DV may = naturally occurring

Ethical
Greater external validity
Natural event may only occur rarely
Ptps not randomly allocated

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21
Q

Quasi Experiment

A

IV based on pre-existing difference e.g., age / gender
No one has manipulated the variable
DV may be naturally occurring or be measured by the experimenter

High control
Comparison can be made between ppl
Ptps not randomly allocated
Causal relas not established

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22
Q

Population Vs Sample

A

Population = large group of ppl the researcher is interested in investigating
Sample = usually not possible to include all population in study so smaller group is selected

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23
Q

Opportunity Sample

A

Ppl who are the most available and willing at the time
= quick but biased

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24
Q

Volunteer Sample

A

Ptps select selves for study
Ptps = willing but is likely to = biased

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25
Random Sample
Every person in the target population has an equal chance of being selected e.g., names in hat = unbiased but not necessarily representative
26
Systematic Sample
Ptps are selected using set pattern e.g., every ninth person from list of target population Is unbiased but = time and effort
27
Stratified Sample
Ptps are selected according to frequency in the target population E.g., a strata (sub-group) is identified and then a random sample selected from each = representative but strata won’t reflect all personal differences
28
Informed Consent
Ptps should be able to make informed judgement about whether to take part Too much info may affect behaviour so alternative forms of consent = ask similar group they consent to being deceived / consent after
29
Deception
Deliberately misleading or withholding information so consent is not informed Ptps should be debriefed to be told true aim, details that were not given and what their data will be used for and their right to withdraw
30
Protection from Harm
Ptps should be at no more risk that they would be in everyday life Should be given the right to withdraw at any time and reassured their behaviour was typical / normal when being debriefed Counselling should be provided if have been distressed
31
Privacy / Confidentiality
Ptps have right to control info about them is that is evaded confidentiality should be rightly respected If personal details are held they must be protected - usually not taken - refer to using numbers, initials or false names Ptps personal data cannot be shared with other researchers
32
Correlation Vs Experiment
Experiment = researcher manipulates the IV and records the effect on the DV Correlation = no manipulation of variables and so cause and effect cannot be demonstrated - EVs not controlled
33
Association
Correlations illustrate the strength and direction of an association between two co variables Plotted in scattergram
34
Types of Correlation
Positive = as one variable increase the other increases Negative = as one variable increases the other decreases Zero = no rela between two variables
35
Correlation Evaluation
= useful starting point for research Is relatively economical No cause and effect Method used to measure the variables may be flawed
36
Naturalistic Observation
Takes place where the target behaviour would normally occur High external validity Low control
37
Controlled Observation
Some control/ manipulation of variables including control of EVs Can be replicated May have low external validity
38
Covert Observation
Ptps are unaware they are being studied Reduced DCs Ethically questionable
39
Overt Observation
Ptps aware are being studied More ethically acceptable DCs
40
Participant Observation
Researcher becomes part of the group they are studying Leads to greater insight Loss of objectivity
41
Non-Participant Observation
Researcher remains separate from the group More objective Loss of insight
42
Behavioural Categories
The target behaviour to be observed should be broken up into a set of observable categories Similar to operationalisation But difficult to make clear Dumped behaviours go unrecorded
43
Time Sampling
Observations made at regular intervals eg., once every 15 seconds Reduced number of observations May be unrepresentative
44
Event Sampling
A target behaviour/ event is recorded every time it occurs May record infrequent behaviour Complex behaviour is oversimplified
45
Questionnaires
Made up of pre-set list of questions (or items) the Ptp responds to Can be used as part of an experiment to assess the DV Can be distributed to lots of ppl Respondents may be willing to open up Responses may not always be truthful Response bias
46
Designing Questionnaires
Write good questions, avoid jargon, avoid double-barrelled questions and avoid leading questions Closed questions = respondent has limited options = easier to analyse but = restrictive Open questions = respondent provide own answers expressed in words, respondents not restricted, difficult to analyse
47
Interviews
Face to face interview between interviewer and interviewee
48
Structured interview
List of pre-determined questions asked in a fixed order Easy to replicate No elaboration
49
Unstructured interview
There are no set questions = general topic to be discussed but the interaction is free-flowing and elaboration is encouraged Is greater flexibility Difficult to replicate
50
Semi-structured interviews
List of questions that have been worked out in advance but interviewers are free to ask follow up questions when appropriate
51
Designing an interview
Have a schedule Have a quiet room Build rapport and make sure you abide to ethics
52
Qualitative Vs Quantitative
Qualitative: non-numerical expressed in words e.g., extract from diary = represents complexities, less easy to analyse Quantitative: numerical e.g., reaction time / number = easier to analyse but oversimplifies behaviour
53
Primary Data
First hand data collected for the purpose of the investigation Fits the job Requires time and effort
54
Secondary data
Collected by someone other than the person who is conducting the study = inexpensive Quality may be poor
55
Meta-Analysis
Secondary data that includes combing data from a large number of studies = increases validity of conclusions Publication bias
56
Measures of Central Tendency
Mean: arithmetic average = sensitive, but may be unrepresentative Median: middle value (if two middle calculate the mean) = unaffected by extreme scores, less sensitive Mode: most frequent/common value = relevant to categorical data, an overly simple measure
57
Measures of Dispersion
Range: difference between highest and lowest value = easy to calculate, doesn’t account for the distribution of scores Standard Deviation: measure of average spread around the mean, larger = m spread out, more precise than the range but may be misleading
58
Tables
Raw scores are displayed in columns and rows Summary paragraph beneath explains the results
59
Bar Chart
Categories along x axis and frequency on y axis Height of each column represents the frequency for the item
60
Histogram
Bars touch - data = continuous not discrete Is a true zero
61
Line Graph
Frequency on one axis and categories on the other Often shows how something changes over time
62
Scattergram
Used for correlational analysis Each dot = one pair of related data Both sets must be continuous
63
Normal Distribution
Symmetrical bell-shaped curve Most ppl are in middle Mean, mode and median = in same area
64
Skewed Distribution
Lean to one side because most ppl are at lower/higher end of distribution Positive Skew: most if distribution concentrated towards left of graph leading to long tail on the right Negative Skew: most of the distribution is concentrated towards right meaning long tail on the left
65
Significance
Difference/association between two sets of data is greater than what would occur by chance
66
Probability
A numerical measure of the likelihood that a certain event will occur Acceptance level of probability is p_<0.05 = 5% chance that the results are down to coincidence
67
Calculated value
Value calculated through stats test Compare to critical value to decide whether is significant or not
68
Critical value
Given in table of critical values
69
Sign Test Calculation
The score for condition B is subtracted from Condition A to produce a sign of difference (+ or -). Do this for each Ptp The total number of pluses and the total number of minuses should be calculated​ Ptps who achieved the same score in both conditions should be disregarded and deducted from the N value​ The S value is the total of the less frequent sign​ Critical Value: If the critical value is equal to or less than you S value then it is significant.
70
Peer Review
B4 publication all aspects if investigation are scrutinised by experts in the field Should = objective and unknown to researcher Aims = allocate research funding, validate quality and relevance of research, suggest improvements and amendments Protects quality of published research May be used to criticise rival research Publication bias Ground breaking research may be buried
71
Psychology and the Economy
Findings can benefit economic prosperity Research into attachment and the role of the father - promote more flexible working arrangements in the family meaning modern parents are better equipped to contribute more effectively to the economy Mental Illness Treatment- 1/3 of all days off are caused by MI - research means patients can have quicker diagnosis and = therapies and drugs to help manage effectively and return to work
72
Open Questions used when … (questionnaires)
Need opinions and attitudes Not time bound Don’t know expected answer Literate ptps
73
Close questions used when … (questionnaires)
Quick Generates number data for stats Opportunity samples Public places - ppl = rushed
74
Structured questions used when … (interviews)
Time is short Opportunity samples Need number data Uncontroversial topic Adults
75
Unstructured questions used when … (interviews)
Children and vulnerable groups Secretive/ unknown behaviour Traumatic/ upsetting topics Personal information
76
Disadvantages of Self Report
Validity issues: not proper interval scale as spaces between numbers = not known/ individually devised, only as good as the questions Investigator bias Social desirability DCs
77
Content Analysis
An indirect way of studying behaviour by looking at what humans create e.g., posters etc Involves generating themes of codes to analyse the behaviour behind the material Normally qualitative data
78
Case Studies
Single Ptp or small group = single place / organisation = in-depth Describes but doesn’t explain Not just a snapshot = more detail Relies on less scientific methods e.g., interviews and self reports - bias = possible Not easily generalisable
79
Controls
Keep the DV uncontaminated so is only changed by IV Environment - stop distractions and interruptions Procedures - anonymised data, standardisation of materials and actions, counter balance effects Design - randomisation of selection to conditions
80
Investigator bias / effect
Any influence the investigator / experimental situation has on ptps - might alter the results & is not intended Ptps might not act naturally if know they are being watched Investigators mood / demeanour may encourage / discourage ptps Single blind / standardisation can counter
81
Demand Characteristics
Can be dealt with using independent groups, or not telling true aim but = ethical concerns
82
Social Desirability
Changing behaviour for fear of being judged Not all behaviour is socially sensitive e.g., memory digit spans Includes topics such as: sexual behaviour, criminal behaviour, parenting and relationships Can be dealt with/ by reassuring info is confidential and anonymous
83
Issues w/ research
Validity, internal and external Reliability, internal, external & inter-rater DCs and investigator effects Ethics’s including the British Psychological Society’s code of ethics, ethical issues in the design and conduct and dealing w/ ethical issues
84
Internal Reliability
Split half method used to ensure reliability of written ability tests such as IQ Makes sure = consistent throughout
85
External Reliability
To improve need to repeat tests over and over again to see what happens to results - using same ptps = test re test Observers collecting data need to be reliable and so have to = trained and use checklists and coding systems to held = inter-rater reliability
86
Internal Validity
Do the tools used to measure the IV & DV / co variables accurately measure them E.g., thermometer accurately measures temperature and nothing else
87
External Validity
A tool is also not valid if it only measures things in labs and not in real life settings = lack of external validity
88
Checking validity
Compare results with previous theories = construct validity Comparing results with previous established tests/ research = concurrent validity Asking informed people if it looks right = face / content validity
89
Type I Error
A false positive and occurs more when a lot of scope for chance - 10% ( make it too easy to show a significant result)
90
Type II Error
A false negative and occurs when you don’t allow much chance - 1% ( make it too hard to show a significant result)
91
Implications of Research for the Economy
Treatments could = waste of money if not effective / good quality (valid) NHS is funded by taxpayer money Anything leading to a loss of productivity in the workplace = loss of money Good research into wellbeing could save money
92
Nominal Data
Simple frequency headcount (number of times something occurred) Found in discrete categories (something can only be in one category) Most simple data E.g., number of people who did / didn’t help in an emergency
93
Ordinal Data
Measurements that can be put in order, rank / position Intervals between are unknown e.g., how far away 2nd was from 1st in a race
94
Interval Data
Measurements on a scale - intervals are known and equal Can go into negative values = most precise E.g., temperature
95
Ratio Data
Measurements in a scale Intervals are known and equal Has true zero - can’t go into negatives most precise E.g., length or time
96
Inferential Stats Test
Used to find out chance of chance - is the result significant? Used w/ repeated measure design and nominal data Result is the sum of the least frequent sign
97
Theory Construction
Scientific process starts with observation Induction model states scientists develop a testable hypothesis Hypothesis = tested leading to new questions & new theories e.g., newtons laws Deduction model involves reasoning & theory 1st & finding instances to support e.g., Darwin
98
Generation of Laws & Principles
Popper (1969) argued theories should = falsifiable Abstract theories = impossible to prove well though empirical research Claimed theory = scientific if falsifiable - can be proved wrong Freud can’t be Kuhn (1962) argued science should have a paradigm - should have key assumptions - a paradigm = reductionist idea m complex can = reduced to smaller level - bio approach
99
Paradigm Shift
Kuhn (1962) argued = 3 stages to science: Pre-science - isn’t science bc = lots of competing approaches Normal science - an overall paradigm = estab to which = gen agreement & appropriate research method Scientific rev - research evidence that challenges the current paradigm so returns to normal science stage So according to Kuhn psych was not a science in the 60s but is now
100
Sign test
N - any that scored same score so = 0
101
Chi-squared
Df = (rows-1) x (column -1) = usually 1
102
Wilcoxen
N - any scores that = same in dif condition
103
Mann Whitney
Na is number of across ptps in condition A and down is Nb is the number of ptps in condition B
104
Related T test
N-1
105
Unrelated T test
NA + NB (number of scores in 1st condition + number of scores in 2nd condition)
106
Spearman’s
Number of sets of scores
107
Pearson’s
N - 2