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

Chapter 1 Research methods Flashcards

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
advantages of controlled experiment
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
26
disadvantages of controlled experiment
*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.
27
classification and identification
-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.
28
generalisability
the extent to which research findings can be applied to the population of interest
29
random sampling
uses a chance process to ensure every member of the population of interest has an equal chance of being selected for the sample
30
disadvantages of random sampling
* 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.
31
advantages of random sampling
* 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.
32
Stratified sampling
Used to ensure that a sample contains the same proportions of participants from each social group present in the population of interest
33
advantages of stratified sampling
The most likely to produce a representative sample.
34
Disadvantaged of stratified sampling
* It can be time-consuming and expensive. * It can be demanding on the researcher to select the most appropriate strata to account for.
35
large sample
more likely to represent the population of interest which improves generalisability and means a relationship is more likely to be found
36
small sample
may affect the accuracy and precision of data collected
37
drawing conclusions
-describing and explaining the results of a study -discussing how the findings relate to the aim and hypothesis
38
a conclusion involves
-justifying claims about whether or not the results support hypothesis -carefully consider the extent results can be generalised to population of interest
39
limitations
consider issues and unexpected problems that may have compromised the internal and external validity of the investigation
40
recommendations
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
fieldwork
observing and interacting with a selected environment beyond the classroom or laboratory
42
modelling and simulation
creating a conceptual, mathematical or physical representation of a system of concepts, events or processes
43
Product, process or system development
the design or evaluation of a process, system or artefact to meet human need
44
within subjects design
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
advantage of within subjects design
*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
limitation of within subjects design
*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
between subjects design
scores are compared between different participants -experimental group compared to control group
48
limitations of between subjects design
-assumes the variation between the two groups is similar (confounding variable) -May require more participants than a within-subjects design.
49
advantages of a between subjects design
-no order effect -faster to complete because dv is only measured once
50
random allocation
minimises the chance of extraneous participant variables becoming confounding variables
51
counterbalancing
-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
extraneous variable
An extraneous variable is any variable that is not the independent variable but may cause an unwanted effect on the dependent variable
53
confounding variable
a variable that has directly and systematically affected the dependent variable, apart from the independent variable
54
placebo
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
single-blind procedure
a procedure in which participants are unaware of the experimental group or condition they have been allocated to
56
double blind procedure
a procedure in which both participants and the experimenter do not know which conditions or groups participants are allocated to
57
purpose of single blind procedure
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
purpose of double blind procedure
This helps to prevent the extraneous variables of experimenter and participant expectations.
59
accuracy
how close a measurement is to the true value of the quantity being measured
60
true value
the value, or range of values, that would be found if the quantity could be measured perfectly
61
precision
how closely a set of measurement values agree with each other
62
systematic errors
errors in data that differ from the true value by a consistent amount -affects accuracy
63
systematic errors may occur because of
* environmental factors * observational/researcher error * incorrect measurement instrument calibration
64
random errors
errors in data that are unsystematic and occur due to chance. -precision of measurement is affected
65
random errors may occur due to
* 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
Random errors may be reduced by:
* repeating and conducting more measurements * calibrating measurement tools correctly * refining measurement procedures * controlling any other extraneous variables * increasing the sample size of participants
67
uncertainty
the lack of exact knowledge relating to something being measured due to potential sources of variation in knowledge
68
repeatability
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
reproducibility
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
validity
the extent to which psychological tools and investigations truly support their findings or conclusions
71
internal validity
the extent to which an investigation truly measures or investigates what it claims to
72
external validity
the extent to which the results of an investigation can be applied to similar individuals in different settings
73
measures of central tendency
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
mean
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
outliers
-negatively impact validity of experiment -make the mean a less accurate summary of the average data value.
76
median
-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
mode
-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
measures of variability
statistics that summarise and describe the spread and distribution of a data set -range -standard deviation
79
range
-The range is used to summarise the overall dispersion (distribution) of scores.
80
standard deviation
-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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