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Component 2 Flashcards Psychology > C2 AO1 definitions > Flashcards

C2 AO1 definitions Flashcards

1
Q

Aim of the research

A

A broad statement of the purpose of the research.

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2
Q

Alternative Hypothesis

A

A testable statement that a piece of research attempts to support or reject.

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3
Q

Directional Hypothesis

A

A hypothesis that suggests there will be a difference/relationship between variables, where the IV will affect the DV in one specific direction/outcome e.g. alcohol slows reaction time.

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4
Q

Non-Directional Hypothesis

A

A hypothesis that suggests there will be a difference/relationship between variables, the IV will affect the DV, but does not state a specific direction/outcome for results e.g. alcohol affects reaction time.

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5
Q

Null Hypothesis

A

A hypothesis that suggests there will be no difference/relationship between variables, any that does occur does so by chance e.g. alcohol will have no effect on reaction time.

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6
Q

Independent Variables (IV)

A

The variable the psychologist manipulates and controls to see how it affects behaviour.

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7
Q

Dependent Variables (DV)

A

The variable which is measured (usually the participants’ behaviour) by the psychologist.

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8
Q

Co-variables

A

Co-variables indicate two or more quantities being measured in a correlation by the researcher that may or may not vary with each other.

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9
Q

Operationalisation of Variables

A

Giving a precise definition of the behaviour being manipulated/observed/measured (IV/DV). This allows for repetition and raises reliability as it is an agreed value that has been attributed to the measurement

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10
Q

Confounding Variable

A

Variables in a study that are not being measured or manipulated by the researcher, that affect SOME participants’ behaviours but not others, having negative consequences for validity.

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11
Q

Extraneous Variables

A

Variables in a study that are not being measured or manipulated by the researcher but affect the results (DV) of ALL participants’ behaviour equally.

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12
Q

Experiments

A

A research method where cause and effect is measured, through the control and manipulation of key variables, and where the participants are randomly allocated to experimental/control groups.

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13
Q

Quasi-Experiments

A

A research where the experimenter has NOT deliberately manipulated the IV and participants are NOT randomly allocated. Methods within this category include natural experiments and difference studies.

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14
Q

Natural Experiments

A

A research method where the IV arises naturally, although the DV can still be measured in a laboratory or any other location of the researcher’s choice. This method would be used when it is unethical to directly manipulate the IV.

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15
Q

Participant Observations

A

A research method where the researcher takes on the role of a participant whilst observing other participants’ behaviour around them.

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16
Q

Non-participant Observations

A

A research method where the researcher watches and records participants’ behaviour without interfering in any way (from a distance).

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17
Q

Content Analysis

A

A research method which involves exploration of behaviour to see what categories, codes or themes emerge, and tallying each time material fits a theme. It converts qualitative data into quantitative data so that it can be more easily compared.

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18
Q

Structured Interviews

A

A research method that includes standardised questions (like in a questionnaire), which are known as an interview schedule, and are usually asked face to face.

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19
Q

Questionnaires

A

A research method that includes a list of written questions, which generate closed and/or open answers. These can be used in person, on-line or through other methods e.g. postal.

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20
Q

Semi-structured Interviews

A

A research method which involves asking participants questions, usually face to face. These can be in the form of an interview schedule, but could also include follow up questions to expand on answers of the questions asked.

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21
Q

Correlational Studies

A

A research method which involves a comparing two continuous variables (co-variables) to see if there is an association/relationship between them.

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22
Q

Case Studies

A

A method which involves an in-depth investigation of a phenomenon, which uses a descriptive analysis of a person, group or event. It is a holistic study through one or more methodologies that is usually longitudinal.

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23
Q

Self-Reports

A

A method which involves a participant reporting on their own thoughts and feelings though methods such as interviews or questionnaires

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24
Q

Quantitative Data

A

A type of data that can be measured numerically by the psychologist, so that statistical analysis can be completed e.g. scores on an IQ test.

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25
Qualitative Data
A type of data that can be observed, but not measured numerically. It usually takes the form of words, thoughts and feelings, and is difficult to analyse e.g. a participants feelings about school.
26
Primary Sources
Information sources/data that is directly collected by the researcher first-hand e.g. they collect data through a questionnaire, experiment, interviews etc. for their research.
27
Secondary Sources
Information sources/data that have not been directly collected /created by the researcher e.g. use of methods such as content analysis of existing data, or literature reviews.
28
Cross-sectional Studies
A method which involves comparing one group of participants, representing a cross-section of society, against another at the same point in time.
29
Brain Scans
A research method which involves taking images of the living brain to investigate brain function e.g. PET, fMRI and CAT scans.
30
Longitudinal Studies/Research
A method which involves conducting research over a long period of time in order to observe long-term effects of X on a specific behaviour. It may utilise a range of other methodologies such as case studies, interviews etc.
31
Conducting research in a laboratory environment
A location of research where scientific research and measurement can be taken using specialist/large equipment. Conditions and variables are controlled, and procedures are standardised.
32
Conducting research in the field
A location of research outside of the laboratory, in a natural setting e.g. school, hospital, workplace etc. It has lower levels of control over confounding variables than the laboratory, but can still utilise a standardised procedure.
33
Conducting research on-line
A location of research where participants are accessed via the internet/social networks/mobile apps etc. Often involves questionnaires but can also be experimental, correlational etc.
34
Target Populations
The group of individuals that a researcher is interested in studying e.g. people in the UK.
35
Sampling Frames
A group/population that is identified when it is unrealistic to study the whole target population e.g. people in London
36
Random Sampling
A sampling technique where participants are selected from the sampling frame, where everyone has an equal chance of being selected. E.g. Names are pulled out of a hat, or a computer is used to randomly select participants.
37
Opportunity Sampling
A sampling technique where participants are selected at the researcher’s convenience without knowing any details about the sample in advance e.g. picking people who were there at the time, in your specific location.
38
Systematic Sampling
A sampling technique where every nth person on a list is selected by the researcher e.g. every 3rd house on a street, or 5th person on a register.
39
Stratified Sampling
A sampling technique where the target group is divided into subgroups, e.g. by sex, and then the participants are selected randomly from each subgroup.
40
Quota Sampling
A sampling technique where the target population is divided into subgroups, e.g. by sex, and the participants are chosen from each subgroup at the convenience of the researcher.
41
Self-Selected Sampling
A sampling technique where participants volunteer (select themselves) for research e.g. they come forward/respond to the psychologist after reading an advertisement in a newspaper or on a notice board.
42
Snowball Sampling
A sampling technique where participants are initially recruited by the psychologist and then those participants recruit further participants from people they know, therefore the sample group appears to ‘snowball’.
43
Observational Sampling Techniques
A sampling technique that is used to collect data about specific behaviours or events within specific time frames.
44
Event Sampling
Where participants are observed by the psychologist, who records a specific behaviour (event) each time it occurs to create a total score
45
Time Sampling
Where the psychologist observes and records behaviour (such as a score) at specific time intervals, e.g. every 15 minutes, and then creates an average score for each participant being observed.
46
Independent groups
An experimental design where participants take part in only one experimental condition
47
Repeated measures
An experimental design where participants take part in both the control and experimental conditions.
48
Matched pairs
A form of independent groups design where the experimental and control participants are deliberately similar e.g. there is a balance between gender and IQ levels in each group/condition.
49
Nominal data
The level of measurement that shows categories of data represented by frequencies. The data sets have no relative numerical value e.g. boys and girls.
50
Ordinal data
The level of measurement where data can be placed into ascending or descending order, but the intervals between data not necessarily equal e.g. the times for first, second and third in a race.
51
Interval data
The level of measurement that has equal numerical intervals between scores e.g. temperature. The interval between 1 and 2 degrees is the same as between 21 and 22 degrees.
52
Ratio data
The level of measurement that has equal intervals between scores and has an absolute or true zero point e.g. speed (mph)
53
Internal reliability
The extent to which a test or measure is consistent within itself e.g. the use of a standardised instructions and procedure for all participants.
54
External reliability
The extent to which a test produces consistent results over several occasions.
55
Ways of dealing with reliability
A measure which improves consistency and accuracy within the results e.g. the use of a standardised procedure or measures such as counterbalancing.
56
Assessing reliability
Measures used to check the consistency of a set of results.
57
Inter-rater reliability
Where two or more psychologists produce consistent results by using a standardised procedure, agreed coding system, or correlation of their data.
58
Test-retest reliability
Involves testing and retesting the same participants over time, with the same test, and comparing their scores. If the scores are the same the test has external reliability.
59
Split-half reliability
Involves splitting a pp’s test answers in half and seeing whether s/he got the same or similar scores on the two halves. If so, internal reliability is high; if not, it is low and individual questions would need to be redesigned.
60
Internal validity
The findings are accurate and the effects on the DV are caused by the IV. Therefore the study measures what it intends to measure (as confounding variables have been controlled and will not affect the results).
61
External validity
Whether the study paints a true picture of real life behaviours (e.g. if the tasks have mundane realism) and whether the findings would apply to different places, different times, or different people (population validity).
62
Specific validity issues
Factors that could cause problems with validity such as researcher bias, social desirability bias and demand characteristics.
63
Researcher bias
Where the researcher either directly or indirectly influences the results of a study, through the process of designing the study or through the way the research is conducted/analysed
64
Demand characteristics
A type of confounding variable where participants unconsciously work out the aim and act differently (either through social desirability or the screw you effect)
65
Social desirability
Where participants give the response that they think will show them in the best possible light. This may mean that they are not a true reflection of their real thoughts/feelings.
66
Ways of dealing with issues of validity
Improving validity through methods such as double or single blind procedures, or through changing the location/nature of the research tasks to make them more reflective of real life.
67
Assessing validity
Methods of checking the internal or external validity of a study.
68
Concurrent validity
Validating a measurement by comparing it with an established measurement that has known validity. If similar results occur on both tests, then this new test is valid. If not, then the new test would have to be redesigned and tested.
69
Construct validity
The most sophisticated test of validity as it looks at whether the overall results reflect the phenomena as a whole (external validity). Checking the existing definitions of the behaviour being studied and redesigning the test if it measures a different construct.
70
Content validity
This objectively checks the method of measuring behaviour is accurate and decides whether it is a fair test that achieves the aims of the study (internal validity). Ask an expert in that specific area of behaviour to check the test is valid.
71
Predictive validity
The degree to which a test accurately forecasts a future outcome on a more broadly related topic. Do the findings apply in different and more varied situations? E.g. Do those with high IQ score gain higher grades in exams?
72
Face validity
The least sophisticated measure of validity. This validity is simply whether the test appears to measure what it claims to, and hence is subjective. Tests where the purpose is clear, even to naïve respondents, are said to have this validity.
73
Confidentiality
Third parties should not be able to trace information back to individual participants. This is usually achieved through providing anonymity e.g. using participant numbers not names.
74
Deception
Deliberately misleading or falsely informing participants about the nature of research.
75
Risk of stress, anxiety, humiliation or pain
Research could induce more than minimal pain through repetitive or prolonged testing. Invasive testing, such as the administration of drugs, or vigorous physical exercise, would not usually be encountered in everyday life, thus is unethical.
76
Risk to the participants’ values, beliefs, relationships, status or privacy
Research that is likely to face this type of risk focuses on socially sensitive topics (e.g. sexuality) and includes potentially sensitive data (e.g. confidential documents).
77
Valid Consent
Includes giving participants enough information (in a form they can understand) so that they can make an informed choice about whether they wish to participate.
78
Working with vulnerable individuals (including children)
Children under the age of 16, those lacking in mental capacity, people in care, people in custody (prison) or on probation, and people engaged in illegal activities, such as drug use, would be categorised in this way.
79
Working with animals
Research with non-human species is strictly controlled. Restrictions on type of animal, care, number of animals required etc. are all controlled by ethical guidelines and laws such as the Animals Act (1986).
80
Ways of dealing with ethical issues/Managing the risk posed by ethical issues
Methods such as ethical committees and guidelines.
81
Ethics committees
Provide a set of moral principles that guide research from its inception through to completion and publication of results.
82
Ethical guidelines
The board that is in place to ensure that proposed research meets the standards of the current ethical codes of conduct and guidelines.
83
Debriefing
A method which aims to ensure participants are aware of the true nature of the study (overcoming any deception). It should return the participant back to their original state.
84
Chi-squared test
A statistical test that is used when the experimental design is independent groups, when the level of data is nominal and when the hypothesis is predicting a difference between variables. The observed value must be higher than the critical value for results to be considered statistically significant.
85
Mann Whitney U test
A statistical test that is used when the experimental design is independent groups, when the level of data is at least ordinal and when the hypothesis is predicting a difference between variables. The critical value must be higher than the observed value for results to be significant.
86
Sign Test
A statistical test that is used when the experimental design is repeated measures/matched pairs, when the level of data is nominal and when the hypothesis is predicting a difference. The critical value must be higher than the observed value for results to be considered statistically significant.
87
Spearman’s rank order correlation coefficient
A statistical test that is used when the level of data is at least ordinal and is related, and when the hypothesis is predicting a correlation/relationship between variables. The observed value must be higher than the critical value for results to be considered statistically significant
88
Wilcoxon matched pairs signed ranks test
A statistical test that is used when the experimental design is repeated measures/matched pairs, when the level of data is at least ordinal and when the hypothesis is predicting a difference between variables. The critical value must be higher than the observed value for results to be significant.
89
Probability Values
A numerical value that gives an indication of the likelihood that results are due to a real difference/correlation and not due to chance e.g. in psychology we accept a probability value of 95%, where results are due to chance in 5% of cases.
90
Significance levels
A numerical value that is usually expressed in value including two decimal places. This level tells you the margin of error that could occur in your results e.g. 0.05 suggests that there is a 5% possibility that results are due to chance and not the difference/correlation between variables.
91
Observed (calculated) Values
The numerical value that is created as a result of inferential statistical analysis of your data. This will be compared to the critical values for the test to calculate the level of significance.
92
Critical Values from tables
The tabulated numerical values that have been assigned to a particular inferential statistical test. It is compared to the observed value for your set of data to calculate significance.
93
Frequency tables
A chart/table which shows the rate of occurrence (frequency) for a number of measured values/categories.
94
Graphical representation
A range of diagrams that show the rate of occurrence for a number of measured values/categories.
95
Bar chart
A diagram that represents frequencies of non-continuous data.
96
Line graphs
A diagram that shows a linear representation of frequencies of data.
97
Histograms
A diagram that represents the distribution of frequencies for discrete or continuous data.
98
Pie charts
A diagram that represents data proportionately, as part of a whole picture of responses.
99
Scatter diagrams
A diagram that represents a relationship/correlation between two or more co-variables.
100
Distribution curves
Linear representations of data that include a mean, median and modal score to show a spread of data.
101
Normal distribution
A type of distribution where the mean, median and mode are equal. This can be referred to as a bell curve.
102
Negative skewed distribution
A type of skewed distribution, where the mode is greater than the mean.
103
Positive skewed distribution
A type of skewed distribution, where the mode is less than the mean.
104
Measures of central tendency
A form of estimation of a mid-point/average in a set of data.
105
Mean
The average that is shown by all scores in the data set when they are divided by n.
106
Median
The mid-point in a set of data that has been placed in order.
107
Mode
The most common value within a set of data.
108
Measures of dispersion
A measure that shows the spread of data, whether it is tightly clustered or has a broader spread.
109
Range
A value which shows the spread of data, representing the difference between the lowest and highest scores.
110
Standard deviation
A value which represents the amount of variation of results from the mean score.

Component 2 Flashcards Psychology (4 decks)

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