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Psychology Unit 3/4 > Unit 4 AOS 3 > Flashcards

Unit 4 AOS 3 Flashcards

Research Methods

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1
Q

what is psychology?

A

Psychology is the scientific study of of human mental processes and behaviour

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2
Q

What makes Psychology a Science?

A
  • Relies on and produces empirical evidence (information obtained through direct and systematic observation or experimentation)
  • It’s objective and uses scientific methodologies
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3
Q

how does psychology differ from non scientific ideas?

A

Differs from non-scientific ideas, and includes pseudosciences (beliefs that are falsely regarded as scientific, such as astrology, palm readings etc). Non-science makes claims that cannot be verified through evidence or observation. Usually based on opinion. Instinct, intuition etc.

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4
Q

what does psychology rely on?

A

PSYCHOLOGY RELIES ON THE SCIENTIFIC METHOD

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5
Q

what is the scientific method?

A

The scientific method is a procedure used to obtain knowledge that involves hypothesis formulation, testing, and re-testing through processes of experimentation, observation, measurement, and recording.

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6
Q

what are psychological models and theories?

A

Psychological models and theories explain psychological phenomena. They are generated through scientific research.

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7
Q

what is a theory?

A

A theory is a proposition or set of principles that is used to explain something or make predictions about cause and effect. It is based on research and logic.

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8
Q

what is a model?

A

A model is a representation of a concept, process or behaviour in order to simplify one;s understanding. It is based on scientific theories and ideas.

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9
Q

example of theory?

A

E.g. ‘behaviourism’ theorises that behaviour is learned through interaction with the environment.

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10
Q

example of model?

A

E.g. the GAS model, the Atkinson-Shiffrin Model etc.

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11
Q

what is an aim?

A

The Purpose of a study

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12
Q

important features of an aim?

A
  • It is important to include the dependent and independent variable in this
  • Should be brief and succinct
  • Should include a verb (action word) - investigate, determine…
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13
Q

define variable

A

a condition or component of an experiment that can be measured or manipulated by the experimenter

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14
Q

define independant variable

A

the variable that is intentionally manipulated (controlled, selected or changed) by the experimenter

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15
Q

define depedant variable

A

the variable that is measured to determine the effect of the IV

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16
Q

feautures of DV?

A
  • Usually a measure of performance, a number or score.
  • Easy to identify as (usually) something that can be counted/quantified or compared.
  • Called the DV because whether or not it changes, and the way it changes, ‘depends’ on the effect of the independent variable.
  • effect
  • want to know how it is effected by the IV
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17
Q

features of IV?

A
  • cause
  • want to know it’s affect on the DV
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18
Q

define operationalizing variables

A

specifying how variables will be measured/manipulated

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19
Q

how do you operationalise the IV?

A

Detail about how many, how long, what sort, what you are doing with them.

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20
Q

how do you operationalise the DV?

A

Detail about how you will measure ‘improvement’ and also what specific tests will be used (if you know)

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21
Q

what axis is the DV recorded on?

A

Y axis

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22
Q

what axis is the IV recorded on?

A

X axis

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23
Q

define RESEARCH HYPOTHESIS

A

a testable prediction about the relationship between two variables (how the IV affects the DV)

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24
Q

what is the acronym for a research hypothsesis?

A

PIDD

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25
Q

what must a hypothesis include?

A
  • The Population that the hypothesis will apply to (only if given)
  • BOTH levels of the Independent Variable
  • The Dependant Variable
  • A specific direction/prediction about what will occur
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26
Q

do you need to explain hypothesis?

A

You do not need to justify WHY you are making that prediction within the hypothesis itself. This is what the background info in an introduction section of a report is for.

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27
Q

define CONTROLLED VARIABLES

A

Other 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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28
Q

are controlled variables apart of the investigation?

A

They are not part of the an investigation because a controlled variable is not an experimental variable (only IV and DV are).

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29
Q

define Investigation Methodologies

A

Any of the different processes, techniques and types of studies used to obtain information/data

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30
Q

what are the two types of Investigation Methodologies?

A
  • Types of psychological studies
  • Other processes and techniques
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31
Q

what are the types of psychological studies?

A
  • Controlled experiments
  • Case studies
  • Correlational study
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32
Q

describe other processes and techniques?

A

These may be a step or process as part of a larger study, or just a process and technique used to understand a psychological phenomenon.

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33
Q

what are the other processes and techniques?

A
  • Classification and identification
  • Fieldwork
  • Literature review
  • Modelling
  • Product, process or system development
  • Simulation
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34
Q

define controlled experiment

A

a type of investigation in which the causal relationship between two variables is tested in a controlled environment

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35
Q

features of controlled experiment

A
  • The most scientifically rigorous and strict research methodologies used in psychology
  • The effect of the IV on the DV is tested while aiming to control all other variables
  • Participants are randomly allocated to either a control or experimental group
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36
Q

define control group

A

the group of participants in an experiment who receive no experimental treatment or intervention in order to serve as a baseline for comparison

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37
Q

define experimental group

A

the group of participants in an experiment who are exposed to a manipulated IV

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38
Q

advantages of controlled experiments

A
  • The researcher can infer causal relationships between, and draw conclusions about, specific variables
  • Provides a high level of control of conditions & variables
  • Follows a controlled procedure, so can be repeated testing reliability (repeatability and reproducibility)
  • A hypothesis can be tested faster than in real world settings
  • Extraneous & confounding variables can be minimised/ controlled for
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39
Q

disadvantages of controlled experiments

A
  • Participants response may be affected by the setting, generally not reflective of real life
  • Open to error or experimenter effect
  • Can be time consuming & expensive
  • Confounding/extraneous variables can still occur
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40
Q

what are the controlled experiment designs?

A
  • BETWEEN SUBJECTS (INDEPENDENT GROUPS DESIGN)
  • WITHIN SUBJECTS (REPEATED MEASURES)
  • MIXED DESIGN
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41
Q

what is matched participants design?

A

attempts to control participant differences across experimental conditions by matching participants (in pairs) on a particular relevant characteristic and then dividing into either control or experimental groups so their result can be compared

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42
Q

what do different experimental designs determine?

A

Different designs determine the structure of an experiment in terms of what conditions participants complete. It is picked based on what is most appropriate for a particular research topic.

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43
Q

define between subjects (independent groups design)

A

participants are divided into different groups and complete only one experimental condition

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44
Q

define within subjects (repeated measures design)

A

participants complete every experimental condition

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45
Q

define mixed design

A
  • combines elements of within-subjects and between-subjects designs
  • Participants are in one of two conditions (between subjects) but are also compared within their condition (within subjects).
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46
Q

what is the allocation in a between subjects design?

A

participants are randomly allocated to EITHER the experimental group OR
the control group

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47
Q

what is the allocation in a within subjects design?

A

participants are involved in BOTH the experimental condition AND the control condition

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48
Q

explanation of mixed design?

A

(1) Each participant is allocated to either the experimental or the control condition (the between-subjects design element) and then completes a pre-test to determine their baseline score before. They then complete a post-test to determine whether their score improved (demonstrating the within subjects design element).

(2) A mixed design may also involve two independent variables, whereby one variable is tested through a between subjects design and the second variable is tested through a within subjects design. One of these variables could also be a naturally occurring variable that the researcher has not manipulated, such as age, sex, geographical location or the presence of another particular characteristic

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49
Q

advantage of Mixed design?

A
  • Results can be compared across groups and across individuals
  • Multiple experimental conditions can be compared to a baseline control group
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49
Q

advantage of Between subjects?

A
  • Generally less time consuming than within subjects
  • No order effects
  • Low rate of participant withdrawal as they only complete one condition
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49
Q

advantage of Within subjects?

A
  • Reduces participant related variables compared to between subjects
  • Can be completed with fewer people than between subjects
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50
Q

disadvantage of Between subjects?

A
  • Often requires more participants than within subjects
  • Participant related variables likely to cause issues when comparing groups, reducing validity. Especially if it’s a small sample.
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51
Q

disadvantage of Within subjects?

A
  • May result in order effects (practice or fatigue related)
  • High dropout rate - can impact the outcome
  • Time consuming
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52
Q

disadvantage of Mixed design?

A
  • Can be costly and time consuming
  • Demanding for researchers and assistants to be across multiple methods (experimenter effect may increase)
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53
Q

what are case studies?

A

An in-depth investigation of an individual or small group of a particular phenomenon that contains a real or hypothetical situation and includes the complexities that would be encountered in the real world.

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54
Q

what do case studies include?

A

Includes data collection (psychological or biological on medical history, environmental information, data from interviews and self-reports etc

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55
Q

features of case studies?

A
  • It is not an experiment, therefore there are no variables
  • Often used when information is rare or specific phenomenon is needed, and typically involves an individual or small group
    E.g. those with brain injuries
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56
Q

advantages of case studies?

A
  • Provide detailed information about a specific phenomenon
  • Allow rare phenomena to be examined
  • Can provide rich qualitative data
  • Can act as a basis for further research
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57
Q

disadvantages of case studies?

A
  • Results cannot be generalised to a wider population, due to lack of representation
  • Subject to research bias and errors
  • Cause and effect is difficult to determine
  • Can be very time consuming
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58
Q

steps to scientific method?

A
  1. Ask a question
  2. Research the question
  3. Form a hypothesis
  4. Test with an experiment or investigation
  5. Analyse data and results
  6. Results support hypothesis or Results do not or only partially support hypothesis (If not supported - Results obtained form basis for new research. This could be a brand new hypothesis or a reformulated version of the original hypothesis.)
  7. Communicate results
  8. Reproduce findings
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59
Q

Famous Case Studies in Psychological Research?

A
  • Phineas Gage
  • Genie the ‘wild child’
  • Patient HM
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60
Q

what happened to Phineas Gage?

A

Phineas Gage (1823-1860) was a US railway worker who experienced a traumatic brain injury in which a large iron rod was driven through his head, destroying much of his frontal lobe. The research on Gage involved a case study investigating the effects of frontal lobe damage on a person.

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61
Q

what happened to Genie the ‘wild child’?

A

Genie the ‘wild child’, important for research in language acquisition due to neglect in the Genie ‘the Wild Child’ case, where a child raised in social isolation and who suffered abuse did not develop speech until she was rescued

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62
Q

what happened to Patient HM?

A

Patient HM, had his hippocampus removed to stop seizures. He was left with long-term anterograde amnesia (unable to form new explicit memories)

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63
Q

what is correlational studies?

A

A non-experimental study in which researchers observe and measure the relationship between two or more variables without any active control or manipulation of them.

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64
Q

what is correlational studies aim?

A
  • Understand the relationship or association existing between variables
  • No variable is intentionally manipulated, simply existing variables are observed
  • Identify which factors may be of greater importance and make predictions.
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65
Q

define correlation?

A

Correlation refers to the strength of the relationship between variables (how likely they are to occur together)

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66
Q

what is positive correlation?

A

Positive correlation = variables change together in the same way (both increase or decrease)

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67
Q

what is negative correlation?

A

Negative correlations = variables change in opposite directions (as one increases, the other decreases)

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68
Q

what is zero correlation?

A

Zero correlation = no relationship between the variables

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69
Q

what are the strength in correlation?

A

weak, moderate, strong

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70
Q

advantages of correlational studies?

A
  • There is no manipulation of variable required
  • The direction and strength of a relationship between variables can be determined
  • Secondary data can be used
  • Ideas for future research can be provided
  • Can be conducted in naturalists settings, findings are therefore applicable to real world settings
  • Can be used to determine the repeatability, reproducibility and validity of measurements, and they are often high in external validity
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71
Q

disadvantages of correlational studies?

A
  • No conclusions about cause and effect can be drawn
  • Correlation does not equal or imply causation
  • Can be influenced by extraneous variables
  • A large amount of data is needed
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72
Q

define classification

A

the arrangement of phenomena, objects of events into manageable sets

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73
Q

what does classification enable?

A

Enables psychologists to create theoretical language to form theories, make predictions and inferences and build upon their inquiry (helps psychologists create consistency in their field as well as creating labels or groups for phenomena, uses common language & rules)

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74
Q

example of classification?

A

DSM-V (classification of mental health disorders based on symptoms presented), classifying different emotions - useful for research in person perception, mental health, developmental milestones (identifying problem behaviours in children, classifying typical vs. atypical behaviour)

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75
Q

define identification

A

a process of recognition or phenomena as belonging to particular sets or possibly being part of a new or unique set (ie. assigning certain things to their respective label or group)

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76
Q

example of identification?

A

E.g. identifying a particular set of symptoms/behaviours/ experiences as belonging to the experience of a particular diagnosed mental illness (e.g. Schizophrenia) based on the classification system used in the DSM-V.

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77
Q

advantages of classification and identification?

A
  • Provides a common language to communicate
  • Aids to simplify, explain and describe complex phenomena
  • Helps form theories about labelled phenomena
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78
Q

disadvantages of classification and identification?

A
  • May over-simplify reality
  • Labels and language can be inaccurate and create bias, stereotyping, prejudice or discrimination
  • Classifications may be based on subjective criteria
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79
Q

define fieldwork

A

Any research involving observation and interaction with people and environments in real-world settings, conducted outside of the lab

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80
Q

features of fieldwork?

A
  • Often involves the collection of primary (first-hand data)
  • Conducted through interviews, questionnaires, focus groups and yarning circles or direct observation
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81
Q

examples of fieldwork

A

Examples: observing the effects of different fragrances on shopper behaviour, effects of lighting in hospitals on patient recovery times, levels of conformity in a group setting, levels of obedience in the school yard during recess

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82
Q

advantages of fieldwork?

A
  • Can be conducted in naturalistic settings – increasing ecological validity
  • Can provide detailed data
  • May be used for a broad range of methodologies
  • May occur over an extended period
  • Rich qualitative data can be obtained
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83
Q

disadvantages of fieldwork?

A
  • Can be time-consuming and expensive
  • Generally does not lead to conclusions about cause and effect
  • Due to lengthy procedures in a real-world setting, fieldwork is difficult to replicate in order to verify results (low reliability)
  • Difficult to control the environment and therefore extraneous variables
  • Observed behaviour is subjective and open to interpretation and bias by the researcher
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84
Q

what is a literature review?

A

The processes of collating and analysing secondary data related to the scientific findings and/or viewpoints of others to answer a question or provide background information

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85
Q

what is a literature review used for?

A

Generally used in preparation for an investigation to generate primary data

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86
Q

advantages of literature review?

A
  • Provides background information on specific phenomena that can be used to inform new studies
  • Provides information about current understandings
  • May highlight patterns of knowledge or gaps of knowledge
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87
Q

disadvantages of literature review?

A
  • Can be time-consuming
  • May be difficult if research on a particular topic is lacking
  • Difficult to ensure all research is consulted
  • Selection bias may result
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88
Q

define modelling

A

The construction and/ or manipulation of either a physical model or a conceptual model that represents a system involving concepts to that help people know, understand, or simulate the system

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89
Q

what are the two types of modelling?

A

Physical – a plastic human brain
Conceptual –the multi-store model of memory, Lazarus and Folkman’s transactional model of stress and coping

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90
Q

advantages of modelling?

A
  • May provide explanatory tools
  • Physical modelling supports the research to know, understand and problem solve
  • Aids to simplify and explain certain phenomena
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91
Q

disadvantages of modelling?

A

May over simplify or inaccurately represent ideas

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92
Q

define simulation

A

A process of using a model to study the behaviour of a real or theoretical system

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93
Q

features of simulation

A
  • Useful to understand how variables operate in a system
    Example: Neurons in the brain firing or growing in response to learning. A computer program ma be used to model what happens at the micro level.
  • Valuable as it provides a visual representation of otherwise inaccessible phenomena.
  • Most likely used when researchers deem it too complex, impractical or dangerous to test the relationship between variables in reality
  • May also be used for explanation and understanding
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94
Q

advantages of simulation?

A
  • Provides insight into potential circumstance or events
  • Allows difficult things to see to be viewed (e.g. neurons)
  • Allows dangerous or time consuming events/ processes to be seen
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95
Q

disadvantages of simulation?

A
  • Can be time-consuming and expensive
  • Subject to programming and human error
  • May not always be accurate or truly reflect reality
96
Q

product, process or system development definition

A

Design or evaluation of an artefact, process or system to meet a human need. Which may involve technological applications in addition to scientific knowledge and procedures

97
Q

feauture of product, process or system development

A

Used when scientists identify a human need that can be served by technology or scientific knowledge

98
Q

product examples

A

new products being developed to find solution to best aid people to function most effectively - apps, websites programs to support mental health such as SmilingMindApp, Chatbot

99
Q

process examples

A

making laws safely and ethically, enabling safe and ethical organ donations

100
Q

system examples

A

DSM, Greek alphabet for COVID strains to reduce geographical stigma

101
Q

advantage of product, process or system development?

A

Creates products, processes and systems that meet a human need

102
Q

disadvantage of product, process or system development?

A

Can be expensive and time-intense

103
Q

define population

A

A population is the larger group of research interest from which a sample is drawn

104
Q

why is population made into a sample?

A

For practical reasons, we cannot test everyone in the population

105
Q

define sample

A

A sample is a subset of the population and refers to the participants that will be involved in the study

106
Q

define representative sample

A

A representative sample accurately reflects the relevant characteristics in the population. If a sample is representative, then it is more likely that the results can be generalised to the wider population

107
Q

what is a representative sample influenced by?

A

This is influenced by sample size, a large sample is more likely to be representative (as a general rule population sizes greater than 1000, sample size should be at least 10% of the population size, for smaller populations, reseearchers shold aim to use more than 30% of population). Any sample size smaller than 100 is deemed very small.

108
Q

Sampling techniques to select participants?

A
  • Random sampling
  • Stratified sampling
  • Convenience sampling (not directly assessable)
109
Q

define convenience sampling

A

Convenience sampling is when subjects are picked based on their availability at the time of the experiment. Quick, easy, cost effective.

110
Q

what type of sample does convenience sampling produce?

A

This will always present a biased sample. They may not be representative of the population (not everyone in the pop. has an equal chance of being selected)

111
Q

benefits of convenience sampling?

A

Time efficient & cost effective

112
Q

limitations of convenience sampling?

A

biased sample, likely that sample is not representative of the population, therefore will compromise the generalisability of the results to the wider population

113
Q

define RANDOM SAMPLING

A

A systematic procedure in which every member of the population has an equal chance of being selected

114
Q

ways to perform random sampling

A
  • Using a random number generator
  • Pulling names out of a hat
115
Q

advantages of random sampling?

A
  • The sample can be more representative than using a convenience sample
  • Sample is generally fairly representative if the sample is large increasing external validity
116
Q

disadvantages of random sampling?

A
  • May be time consuming to ensure every member of the population has an equal chance of being selected
  • If a small sample is generated, it may not be very representative reducing external validity
117
Q

define STRATIFIED SAMPLE

A

Dividing the population into smaller groups known as strata based on shared characteristics and allocating equally between the control and experimental groups

118
Q

steps of STRATIFIED SAMPLE?

A
  1. Divide the population into different strata based on characteristics relevant to the study
  2. Select participants from each stratum in proportion to how they appear in the population
119
Q

advantage of stratified sampling?

A

More likely than random sampling to produce a representative sample, improving external validity

120
Q

disadvantage of stratified sampling?

A
  • Can be time consuming and expensive
  • Can be demanding on the researcher to select the most appropriate strata to account for
121
Q

define Extraneous variable

A

any variable other than the IV that may cause an unwanted effect on the DV

122
Q

what can EV’s be?

A

EV’s can be individual participant differences (ie. Intelligence levels, mood), experimenter effects (ie non-standardised instructions), or situational variables (ie uncomfortable sleep lab).

123
Q

what must you do if you have EV’s?

A
  • You must attempt to control or eliminate these variables before conducting your research, otherwise you may have problems drawing conclusions.
  • Should be controlled (kept constant) or monitored, or the internal validity of the investigation may be reduced and they become confounding variables
124
Q

define Confounding variable

A

a variable other than the IV, that has directly and systematically affected the DV

125
Q

what do confounding variables do?

A

These variables interfere with the internal validity of the investigation, as they provide alternative explanations for the investigation results

126
Q

TYPES OF EV/CV’S?

A

D - Demand Characteristics
O - Order Effects
P - Participant differences
P - Placebo Effects
E - Experimenter Effects
N - Non-Standardised Procedures
S - Situational Variables

127
Q

define Demand characteristics

A

Refers to cues in an experiment that may signal to a participant the intention of the study and influence their behaviour

128
Q

examples of Demand characteristics

A

E.g. asking participants to complete a questionnaire at the start of the the study about their ability to concentrate. This signals that the study is testing concentration, so may conduct themselves/ change behaviour to be more highly alert. Others: Acting differently, trying harder, changing the way you conduct yourself because you know you are being observed

129
Q

define Order Effects (in a within-subjects design)?

A
  • Might occur when the sequence in which a person does the tasks affects their performance on the tasks.
  • This could be seen through either improving performance on second task due to practise (known as practice effects), or worsening due to fatigue or boredom.
130
Q

what does order effects cause?

A

This would confound results, creating a false reading of the effect of the IV on the DV.

131
Q

define Participant Differences (in a between-subjects design)

A

Each person brings with them to an experiment their own individual differences that can affect the results.

132
Q

examples of Participant Differences

A

Examples could include: gender, age, intelligence, memory ability, brain injury, health, experience on a particular task or occupation, sleeping patterns.

133
Q

what happens if particular differences are not controlled?

A

If particular differences are not controlled for, these may cause a change in the DV.

134
Q

define Placebo Effects

A

where participants will behave differently due to their own expectations about the treatment they are receiving.

135
Q

example of Placebo Effects?

A

For example, if participants in the experimental group are given a smart pill and the control group is given no pill, the experimental group may perform better because they have been given something they believe will make them smart. Likewise the control group may perform worse because they believe they have been given no treatment.

136
Q

define Experimenter Effect/Bias

A

Occurs when there is a change in the participants behaviour as a result of the interaction or influence with the experimenter or researcher. (e.g. providing encouragement, favouritism etc)

137
Q

what can Experimenter Effect/Bias do?

A

This could influence how the research is conducted or how findings are interpreted

138
Q

examples of Experimenter Effect/Bias

A

This could be treating the experimental group differently to the control group, or dropping hints about what results they would expect to see. (This might be done unintentionally)

139
Q

define Non-Standardised Instructions and Procedures

A

EV’s can occur if there are differences in the way the experimenter (or each experimenter if there is more than one) conducts their experiment each time they run it.

140
Q

example of Non-Standardised Instructions?

A

This could be differences in the procedures carried out or the instructions given to participants. These should be consistent across all groups.

141
Q

what can Non-Standardised Instructions lead to?

A

If there are differences in administration each time, then this is an example of the research being non-standardised. This will make it hard to draw any conclusions because there is no consistency in experimentation.

142
Q

define Situational Variables

A

Refers to any environmental factor that may affect the DV

143
Q

examples of Situational Variables

A

E.g. Temperature, Lighting, Weather, Time of Day

144
Q

what happens is situational variables aren’t controlled?

A

If not controlled or eliminated, can become an EV/CV

145
Q

how to prevent participant differences?

A
  • Selecting an appropriate sampling procedure (stratified or random)
  • Having a larger sample size
  • Choosing a within subjects experimental research design. Not between-subjects!
  • Controlling variables
146
Q

how to prevent order (practice) effects?

A
  • Counterbalancing (splitting participants in half and each half completes the conditions in different orders to avoid practice effects or boredom/fatigue)
  • Choosing another experimental research design (not within-subjects)
147
Q

how to prevent placebo effect (participant expectations)?

A
  • Using a placebo (a fake inactive substance)
  • Single-blind procedures (procedure where participants are unaware of whether they are in control or experimental group)
148
Q

how to prevent experimenter effects/bias?

A

Double blind procedures (both the participants and the experimenter do not know which group (experimental or control) the participants are allocated to. (usually a research assistant knows)

149
Q

how to prevent non-standardised instructions & procedures?

A

Standardise instructions and procedures (ie. make all instructions and processes consistent)

150
Q

how to prevent demand characteristics?

A
  • Double-blind procedure
  • Standardised instructions and procedures
151
Q

how to prevent situational variables?

A
  • Controlling variables
  • Standardising testing conditions and procedures (e.g same time of day, constant room temp etc).
152
Q

define Primary data

A

collected through first-hand experience

153
Q

define Secondary data

A

obtained second hand through research or data collected by another person for another purpose

154
Q

features of primary data?

A
  • Useful as it can be tailored to the specific purpose of the investigation
  • Can be costly and time consuming
155
Q

features of secondary data?

A
  • Can be used when it is not possible to collect primary data because of time or cost, or lack of availability
  • Can provide a baseline to compare primary data against
  • Cost and time effective
156
Q

define Qualitative data

A

describes characteristics and qualities (non-numerical)

157
Q

features of Qualitative data?

A
  • Measures that are not numeric E.g. words, photographs, videos audio and other recordings
  • Results can be rich in detail
  • Difficult to summarise and then compare
158
Q

define Quantitative data

A

involves measurable values and quantities and can be compared on a numerical scale

159
Q

features of Quantitative data?

A
  • Measurements such as lengths, weight, time, frequency, tallies
  • Can be summarised easily, allowing for comparisons between groups
160
Q

define Objective data

A

factual data that is observed and measured independently of personal opinion

161
Q

features of Objective data

A

-Uses measuring tools which will consistent
-E.g. A person’s weight in kg, IQ score

162
Q

define Subjective data

A

data that is informed by personal opinion, perception or interpretation

163
Q

features of Subjective data

A

-usually comes from the participants own qualitative descriptions and self report methods like surveys, questionnaires
-usually provides rich and detailed data, but very difficult to verify and compare, therefore not used on its own.

164
Q

define descriptive statistics

A

statistics that summarise, organise, and describe data. In other words, they process quantitative data in its raw form and allow it to be described further.

165
Q

what must researchers do before applying descriptive statistics?

A

Before applying descriptive statistics, researchers should account for any missing or incomplete data as this can affect their usefulness and accuracy in summarising data. There are a few methods which can be taken into account for missing or incomplete data depending on what is appropriate for each study, such as deleting the missing or incomplete data cases from the data set.

166
Q

types of descriptive statistics?

A
  • Percentages
  • Measures of central tendency
  • Measures of variability
167
Q

types of Measures of central tendency?

A
  • mean
  • median
  • mode
168
Q

types of Measures of variability?

A
  • Range
  • Standard deviation
169
Q

define Percentage

A

represent a proportion of a whole

170
Q

define Percentage change

A

calculation of the degree of change in a value over time
- Allows comparisons from old and new values

171
Q

define Measures of central tendency

A

Statistics which describe the central value of a set of data

172
Q

what is mean?

A

the average value of a set of data
- Is greatly affected by outliers (extreme values)

173
Q

what is median?

A
  • the middle value in an ordered set of data
  • Not affected by outliers
  • If there is an even number of values, find the mean of the two middle values
174
Q

what is mode?

A

the value that occurs most frequently within a data set

175
Q

Measures of central tendency that is Qualitative data, including categorical data?

A

mode

176
Q

Measures of central tendency that is Quantitative data that is continuous (e.g. height, weight, time, temperature) with a symmetrical distribution?

A

mean, median, mode

177
Q

Measures of central tendency that is Quantitative data that is continuous with a skewed distribution?

A

median

178
Q

Measures of central tendency that is Data with outliers or small data sets?

A

median, mode

179
Q

what is Measures of variability?

A

Measures of variability describe the distribution of the data
E.g. Range, standard deviation

180
Q

define range

A

difference between the largest and smallest value to determine the spread in the data set

181
Q

define Standard deviation

A

describes the spread of data around the mean

182
Q

features of SD?

A
  • How much the data varies
  • A smaller standard deviation suggests that the values are close together (close to the mean)
  • A larger standard deviation suggests that the values are spread far apart from the mean
  • Greater spread, ie. greater SD, can indicate lower validity
183
Q

define Validity

A

refers to the extent to which an assessment tool/ measurement measures what it is designed to measured (In Psychology this refers to how well the results among the participants in the sample represent true findings among similar individuals beyond on the sample)

184
Q

define Internal validity

A

internal validity is achieved if a study investigates what is aimed to/ claims to investigate

185
Q

features of internal validity?

A
  • Influenced by appropriateness of investigation design (did it minimise EV/Cvs?), sampling (is it representative?), allocation (was this random?), extraneous and confounding variables (were there any EV/CV’s?)
  • Lack of internal validity suggests the results deviate from the truth and therefore no conclusions can be drawn
186
Q

define External validity

A

is achieved if the results of the research can be applied (generalised) to similar individuals in a different setting

187
Q

features of external validity?

A
  • Lack of external validity suggests results cannot be applied (generalised) to the population
  • External validity can be improved by using appropriate sampling techniques, making sure the sample is representative of the population (inc. ages, cultural backgrounds etc), using a large sample size
188
Q

Key question of Internal validity?

A

Did the study truly measure what it claimed to?

189
Q

Key question of External validity?

A

Can the study’s results be applied to similar people in other contexts?

190
Q

Area of consideration for Internal validity?

A

Inside the present study

191
Q

Area of consideration for External validity?

A

Beyond the present study

192
Q

define Repeatability

A

the consistency of results of successive measurements of the same quantity being measured under the same conditions (IE. SAME PROCEDURE, OBSERVER, INSTRUMENTS, INSTRUCTIONS AND SETTINGS)

  • You can repeat your experiment and get the same results over and over again
193
Q

define Reproducibility

A

the closeness/ consistency of results of the same quantity/ measure carried out under different conditions

194
Q

features of Reproducibility?

A
  • E.g. the method of data collection, observer, measurement tool or location etc. are changed but measure the same thing
  • Other scientists could follow your method and get the same results over and over again
195
Q

difference between repeatability and reproducibility?

A

REPEATABILITY AND REPRODUCIBILITY ENSURE THAT FINDINGS ARE NOT JUST ONE-OFF ANOMALIES. IF RESEARCH IS REPEATABLE AND REPRODUCIBLE, THEN IT IS CONSIDERED MORE RELIABLE & STRONGER/MORE ROBUST.

196
Q

In depth of accuracy?

A
  • Another consideration when drawing conclusions is accuracy. Experimental accuracy refers to how close the experimental result obtained is to the accepted, or ‘true’, value of the particular quantity subject to measurement.
  • The true value is the value that would be found if the quantity could be measured perfectly.
  • The difference between a measured value and the true value is known as the ‘measurement error’.
  • ‘Accuracy’ is not a quantity and therefore cannot be given a numerical value. It is allowable for a measurement to be described as being ‘more accurate’ when its method and/or instruments clearly reduce measurement error.
197
Q

what is the features of Analysing the quality of data?

A
  • True Value
  • Accuracy
  • Precision
198
Q

what is true value?

A

the value that would be obtained if the quantity was measured perfectly
- Requires no errors when collecting, processing or reporting data

199
Q

what is accuracy?

A

describes how close a measured value is to its true value
- This is not quantifiable, should be described as more or less accurate

200
Q

what is precision?

A

the consistency of data, how close a set of measured values are to each other

  • High precision = the same value is obtained multiple times
  • Note: accuracy can be low but precision high when data points are similar even if far from the true/desired value
201
Q

define errors

A

differences between observed values and the true value

202
Q

define personal errors

A

mistakes or miscalculations made by the experimenter
- E.g. counting incorrectly, rounding to the wrong decimal place or labeling samples incorrectly

203
Q

define Measurement errors

A

the difference between the measured value and the true value

204
Q

what is random errors?

A

caused by unpredictable variation in the measurement process and results in a spread of readings
- Random errors reduce precision

205
Q

what is Systematic errors?

A

cause results to differ from the true value by a consistent amount each time
- Typically, due to faulty equipment and affect the accuracy of the experiment

206
Q

what is Uncertainty?

A

a quantification of the error associated with a measurement often represented by the symbol ‡ after a reading
* Describes a lack of exact knowledge of the value being measured

207
Q

what is Outliers?

A

readings that lie a long way from other results

208
Q

what are Inferential statistics?

A

Inferential statistics allow us to infer cause and effect relationship between variables. They allow us to say that the IV has affected the DV. They allow for a valid conclusion to be formed and generalisations to be made.

209
Q

what calculations are Inferential statistics?

A

They are statistical calculations. One that you need to be able to interpret is the p-value (usually from a t-test).

210
Q

when can you draw conclusions?

A
  • For a conclusion to be made, there should be a statistically significant result.
  • This means you can only draw conclusions if you have been given inferential stats, not descriptive stats.
211
Q

what is statistically significant?

A

If the probability that the results occurred due to chance are less than 5%..ie. the p value is less than 0.05 (p<0.05) then we can say our results are statistically significant. This means they are due to the IV and not due to chance or EV’s/CV’s.

212
Q

what is not statistically significant?

A

If p>0.05 then our results are not statistically significant. This means we cannot draw a valid conclusion because our results are not due to the IV but to chance or other errors. Therefore we reject our hypothesis and no conclusion can be drawn.

213
Q

define conclusions?

A

A conclusion is a decision or judgement about the research results compared to the hypothesis.

214
Q

in depth conculsions?

A
  • Specifically, it will relate back to the hypothesis and whether is has been supported or not, referring to the data or evidence that demonstrates this.
  • Another key part of the conclusion is the extent to which the results can be applied back to the research population (generalisability)
215
Q

are conclusions easily made?

A
  • Often it is difficult to generalise the results from an experiment
  • The constraints of time and cost often means one of the factors (in previous slide) are not met
  • Often, more research is required to build upon the data collected
216
Q

what do researches suggest in a conclusion?

A

In a conclusion, often researchers make recommendations for future research.

217
Q

what do researchers do once they have conducted their initial experiment?

A
  • Often, research is conducted more than once to test if results are replicable (not a one-off) to be able to draw a reasonable conclusion.
  • This can be achieved by repeating (conducting same tests without any change to obtain the same/very similar results) or reproducing (the same tests conducted with different participants and researcher to obtain the same/very similar results) an investigation
218
Q

what is the main goal of psychological research?

A

Generalising to a population is the main goal of psychological research.

219
Q

define generalisation

A

A generalisation is when a research finding can be applied from the sample to the broader population.

220
Q

A generalisation should only be made if the following things are all met?

A
  1. The results must be statistically significant (inferential stats needed!!!)
  2. The sample is representative of the population you wish to generalise to
  3. The sampling method was appropriate (unbiased)
  4. Extraneous and confounding variables have been controlled for to the best of ability (no obvious flaws)
  5. The results are therefore valid and reproducible and repeatable
221
Q

what are the components of a conclusion?

A
  • re state hypothesis
  • reject or agree (supported or not)
  • The results
  • cannot or can be generalised
  • future research considerations
222
Q

define Ethical concepts

A

Broad moral guiding principles that should be considered when conducting research

223
Q

define respect

A

the consideration of the extent to which living things have an intrinsic value and/ or instrumental value; giving due regard to the welfare, liberty and autonomy, beliefs, perceptions, customs and cultural heritage of both the individual and the collective; consideration of the capacity of living things to make their own decisions, ensuring that they are empowered where possible and protected as necessary

224
Q

define integrity

A

the commitment to searching for knowledge and understanding, and the honest reporting of all sources of information and results, whether favourable or unfavourable, in a manner that permits scrutiny and contribution to public knowledge and understanding

225
Q

define justice

A

the moral obligation to ensure that there is fair consideration of competing claims; that there is no unfair burden on a particular group from an action; and that there is fair distribution and access to the
benefits of an action

226
Q

define beneficence

A

the commitment to maximising the benefits and minimising risks and harms involved in taking a particular position or course of action

227
Q

define Non-maleficence

A

the principle of avoiding causing harm. However, as a position of course of action may involve some degree of harm, the concept of non-maleficence implies that the harm resulting from any position of course of action should not be disproportionate to the benefits from any position or course of action
- Sometimes referred to as the no-harm principle

228
Q

how are beneficence and non-maleficence together?

A

These two concepts can be considered together, one must act in a manner that promotes the benefit to others (beneficence), while also minimising harm to others (non-maleficence)

229
Q

define Ethical Guidelines (participants rights)

A

The procedures and principles used to ensure participants are safe and respects

230
Q

acrostic for Ethical Guidelines (participants rights)

A

“Every dumb dog walks in country Victoria”

Every (ethics)
Dumb (deception)
Dog (debriefing)
Walks (withdrawal rights)
In (informed consent)
Country (confidentiality)
Victoria (voluntary participation)

231
Q

define Confidentiality

A

the privacy, protection and security of a participant’s personal information in terms of personal details and the anonym of individuals results, including the removal of identifying elements

232
Q

define use of deception

A

deception is only possible when participants knowledge of the true purpose of the experiment may affect their behaviour whilst participating in the study, and the subsequent validity of the experiment
- The possibility of deception must be outlined in the consent form
- Deception must be fully explain at the conclusion of the study

233
Q

define Informed consent

A

processes that ensure participants understand the nature and purpose of the experiment, including potential risks (both physical and psychological), before agreeing to participate in the study
- Participants must be aware of their rights, the associated risks and the nature of the study prior to agreeing to participate and if under 18 consent must also be given my a legal guardian

234
Q

define Debriefing

A

a procedure that ensures that, at the conclusion of the experiment, the participant leaves understanding the experimental aim, results and conclusions. Any harm must also be addressed and reversed

235
Q

define Voluntary participation

A

no coercion or pressure can be placed on participants to partake in an experiment, and they must freely choose to be involved
- In order to have voluntary participation, there must also be informed consent

236
Q

define Withdrawal rights

A

the right of participants to be able to discontinue their involvement in an experiment at any time during, or after the conclusion of, an experiment without penalty
- Participants results should also be removed

237
Q

what comes under Ethical considerations?

A

Ethical concepts and Ethical guidelines

238
Q

what are the Ethical concepts?

A
  • beneficence
  • integrity
  • justice
  • non-maleficence
  • respect
239
Q

what are the Ethical guidelines?

A
  • confidentiality
  • informed consent procedures
  • use of deception
  • debriefing
  • voluntary participation
  • withdrawal rights

Psychology Unit 3/4 (5 decks)

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