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Psychology Unit 3 & 4 > Chapter 1 Research methods > Flashcards

Chapter 1 Research methods Flashcards

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1
Q

Empirical evidence

A

information obtained
through direct and
systematic observation or
experimentation

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2
Q

Pseudoscience

A

beliefs, theories, and practices that are mistakenly regarded as, or claim to be scientific, but are not because they do not use the methods of science

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3
Q

objective

A

not influenced by personal feelings or opinions in considering and representing facts.

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4
Q

subjective

A

anecdotal information that comes from opinions, perceptions or experiences.

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5
Q

theory

A

a proposition or
set of principles that is
used to explain something
or make predictions about
relationships between
concepts

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6
Q

aim

A

-a statement outlining the purpose of an investigation
-The aim of this study is to investigate the role of high quality sleep on concentration.

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7
Q

Hypothesis

A

a testable prediction that identifies the population and the strength and direction, of a relationship between 2 variables
-identify IV and DV
-directional prediction

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8
Q

Independent variables

A

the variable for which quantities are manipulated by the researcher, and the variable that is assumed to have a direct effect on the DV

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9
Q

Dependent variable

A

The variable the researcher measures in for changes it may experience due to the effect of the independent variable

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10
Q

operationalised variable

A

specifying exactly how the variables will be manipulated or measured in a particular controlled experiment

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11
Q

controlled variables

A

variables other than the IV that a researcher holds constant (controls) in an investigation, to ensure that changes in the DV are solely due to changes in the IV

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12
Q

controlled experiment

A

casual relationship between one or more IV on a DV whilst controlling for all other variables

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13
Q

Primary data

A

first hand collected data from a study you have designed

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14
Q

Secondary data

A

data collected by someone else that you use when conducting a literature review of the existing knowledge on a research topic

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15
Q

Quantitative data

A

-Numerical data
-collected through systematic and controlled procedures to ensure that the measurements are accurate and precise across people and trials

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16
Q

Qualitative data

A

-Non-numerical
-Verbal descriptions of states or qualities that are often organised into themes

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17
Q

sample

A

a group of people who are recruited from a larger population of interest

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18
Q

Correlational studies

A

a non-experimental study where the researcher investigates relationships between variables:
*variables are not controlled or changed
*variables are observed and measured and they naturally occur

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19
Q

Correlation

A

a measure of the strength and direction of the relationship between two variables in a data set

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20
Q

case study

A

an analysis of one particular example in an area of interest that is carried out to develop our understanding of a whole process

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21
Q

advantages of a case study

A

*the data is rich and highly detailed
*can include the complexities that they encountered in the real world

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22
Q

Disadvantages of a case study

A

*the information is specific to those in the case study. The details may not apply to the wider population or to other situations

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23
Q

advantage of correlational studies

A

There is no manipulation of variables required.
* They can provide ideas for future hypotheses
and research, as well as form the basis for
theories.
* They can provide information about the
relationships and associations between
variables.
* They can be conducted in naturalistic settings,
so findings are applicable to real work.

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24
Q

disadvantages of correlational studies

A
  • Their results cannot draw conclusions about cause and effect.
  • They can be subject to the influence of extraneous variables.
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25
Q

advantages of controlled experiment

A

They allow researchers to infer causal
relationships between, and draw conclusions
about, specific variables.
* They provide researchers with a high level of
control over conditions and variables.
* They follow a strictly controlled procedure so
it can be repeated to check results.
* They can allow researchers to test hypotheses
more quickly than in real-world settings.
* The high control of variables may mean
prevention of extraneous and confounding
variables

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26
Q

disadvantages of controlled experiment

A

*As they are often conducted in a laboratory or
highly controlled setting, the setting may not be
reflective of real life. This may affect participants’ responses.
* Because experiments involve human control
and manipulation of variables, they are open to
researcher error or ‘experimenter effects’.
* It can be time-consuming and expensive to
manipulate and measure certain variables.
* Confounding or extraneous variables can still occur.

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27
Q

classification and identification

A

-Classification is the arrangement of phenomena, objects, or events into manageable sets.
-Identification is a process of recognition of phenomena as belonging to particular sets
or possibly being part of a new or unique set.

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28
Q

generalisability

A

the extent to which research findings can be applied to the population of interest

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29
Q

random sampling

A

uses a chance process to ensure every member of the population of interest has an equal chance of being selected for the sample

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30
Q

disadvantages of random sampling

A
  • It may be time-consuming
    to ensure every member of a
    population has an equal chance
    of being selected for the sample.
  • It may not create an entirely
    representative sample when the
    sample is small.
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31
Q

advantages of random sampling

A
  • The sample generated can
    be more representative than
    convenience sampling.
  • It reduces experimenter bias in
    selecting participants.
  • It can make a fairly
    representative sample if the
    sample is large.
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32
Q

Stratified sampling

A

Used to ensure that a sample contains the same proportions of participants from each social group present in the population of interest

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33
Q

advantages of stratified sampling

A

The most likely to produce a representative sample.

34
Q

Disadvantaged of stratified sampling

A
  • It can be time-consuming and expensive.
  • It can be demanding on the researcher to select the most appropriate strata to account for.
35
Q

large sample

A

more likely to represent the population of interest which improves generalisability and means a relationship is more likely to be found

36
Q

small sample

A

may affect the accuracy and precision of data collected

37
Q

drawing conclusions

A

-describing and explaining the results of a study
-discussing how the findings relate to the aim and hypothesis

38
Q

a conclusion involves

A

-justifying claims about whether or not the results support hypothesis
-carefully consider the extent results can be generalised to population of interest

39
Q

limitations

A

consider issues and unexpected problems that may have compromised the internal and external validity of the investigation

40
Q

recommendations

A

should be made for modifying or extending the investigation in future studies and for what further evidence may be needed to make conclusions. This enhances validity of future studies

41
Q

fieldwork

A

observing and interacting with a selected environment beyond the classroom or laboratory

42
Q

modelling and simulation

A

creating a conceptual, mathematical or physical representation of a system of concepts, events or processes

43
Q

Product, process or system development

A

the design or evaluation of a process, system or artefact to meet human need

44
Q

within subjects design

A

each participant’s score is compared to their own score at a different time
-exposed to both experimental condition and controlled condition
-aka. repeated measures design

45
Q

advantage of within subjects design

A

*individual differences between people do not influence the results because each participant is compared to themselves
*Less people are needed because
each participant completes each
experimental condition.
* Good for real-world settings and
phenomena, such as the impact
of certain teaching methods
on learning

46
Q

limitation of within subjects design

A

*susceptible to order effect. They could perform better in second condition
* In addition, a participant
dropping out of a within subjects
experiment has a greater impact
on the study as the experimenter
loses two data points instead
of one.

47
Q

between subjects design

A

scores are compared between different participants
-experimental group compared to control group

48
Q

limitations of between subjects design

A

-assumes the variation between the two groups is similar (confounding variable)
-May require more participants
than a within-subjects design.

49
Q

advantages of a between subjects design

A

-no order effect
-faster to complete because dv is only measured once

50
Q

random allocation

A

minimises the chance of extraneous participant variables becoming confounding variables

51
Q

counterbalancing

A

-ordering experimental conditions in a certain way
-used to overcome order effect
-the order of the conditions is split so not everyone completes the same conditions in the same order
-averages out any potential order effects across both conditions

52
Q

extraneous variable

A

An extraneous variable is any variable that is not the independent variable but may cause an unwanted effect on the dependent variable

53
Q

confounding variable

A

a variable that has directly and systematically affected the dependent variable, apart from the
independent variable

54
Q

placebo

A

Studies that test the efficacy of new drugs or treatment interventions typically have at least
two experimental groups. One group is generally provided with the active substance or
intervention, while another group may be given a placebo.

55
Q

single-blind procedure

A

a procedure in which
participants are unaware
of the experimental group
or condition they have
been allocated to

56
Q

double blind procedure

A

a procedure in which
both participants and
the experimenter do not
know which conditions or
groups participants are
allocated to

57
Q

purpose of single blind procedure

A

single-blind procedures can also minimise demand characteristics, as there are fewer cues
participants can use to infer a study’s hypothesis, and other participant expectations which may influence results

58
Q

purpose of double blind procedure

A

This helps to prevent the extraneous variables of experimenter and participant expectations.

59
Q

accuracy

A

how close a
measurement is to the
true value of the quantity
being measured

60
Q

true value

A

the value, or
range of values, that would
be found if the quantity
could be measured
perfectly

61
Q

precision

A

how closely a
set of measurement values
agree with each other

62
Q

systematic errors

A

errors in data that differ
from the true value by a
consistent amount
-affects accuracy

63
Q

systematic errors may occur because of

A
  • environmental factors
  • observational/researcher error
  • incorrect measurement instrument calibration
64
Q

random errors

A

errors in data that are unsystematic and occur due to chance.
-precision of measurement is affected

65
Q

random errors may occur due to

A
  • poorly controlled or varying measurement procedures
  • imperfect or faulty measurement tools, e.g. a scale that is running out of battery
  • variations in measurement contexts, (results taken in morning and night)
66
Q

Random errors may be reduced by:

A
  • repeating and conducting more measurements
  • calibrating measurement tools correctly
  • refining measurement procedures
  • controlling any other extraneous variables
  • increasing the sample size of participants
67
Q

uncertainty

A

the lack of
exact knowledge relating
to something being
measured due to potential
sources of variation in
knowledge

68
Q

repeatability

A

the extent
to which successive
measurements or studies
produce the same results
when carried out under
identical conditions within
a short period of time (e.g.
same procedure, observer,
instrument, instructions,
and setting)

69
Q

reproducibility

A

the extent to which
successive measurements
or studies produce
the same results
when repeated under
different conditions (e.g.
different participants,
time, observer, and/or
environmental conditions)

70
Q

validity

A

the extent to
which psychological tools
and investigations truly
support their findings
or conclusions

71
Q

internal validity

A

the extent to which
an investigation truly
measures or investigates
what it claims to

72
Q

external validity

A

the extent to which the
results of an investigation
can be applied to similar
individuals in different
settings

73
Q

measures of central tendency

A

descriptive
statistics that summarise
a data set by describing
the centre of the
distribution of the data set
with a single value
-mean
-median
-mode

74
Q

mean

A

The mean is helpful because it can tell a researcher what the typical response or score is. However, the mean is more helpful when data values are distributed around a ‘centre’ (a ‘normal distribution’), and is less helpful when data values are widely distributed, in which case the data set is likely to be influenced by extreme values and outliers.

75
Q

outliers

A

-negatively impact validity of experiment
-make the mean a less accurate summary of the average data value.

76
Q

median

A

-useful for researchers to identify a more typical response when the data is not evenly distributed around the centre, or when there are outliers.
-not outliers or extremely low or high values.

77
Q

mode

A

-least commonly used measure of central tendency, but is useful for knowing the
most common and frequently occurring value.
-helps researchers to understand the
centre of the data set when the mean or median cannot be calculated.

78
Q

measures of variability

A

statistics that summarise
and describe the spread
and distribution of a
data set
-range
-standard deviation

79
Q

range

A

-The range is used to summarise the overall dispersion (distribution) of scores.

80
Q

standard deviation

A

-the standard deviation number shows how much data ‘deviates’ from the mean.
-The higher this value, the greater the data values in the set differ from the mean.
-provides more detailed information about the true nature of a data set compared to the range.
-This primarily allows for an awareness of the differences in participants’ responses.

Psychology Unit 3 & 4 (11 decks)

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