Psyc232 Test 1 Flashcards

1
Q

Identifying phenomena, such as why some individuals fail to stop at red lights.

A

Describing

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2
Q

Formulating hypotheses, e.g., whether wealth influences ethical behavior.

A

Predicting

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3
Q

Developing theories based on collected data to clarify observed behaviors.

A

Explaining

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4
Q

The ultimate aim of many psychological studies is to influence or change behaviors based on findings

A

Controlling

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5
Q

Starts with a theory, formulates a hypothesis, and then collects data to test it.

A

Deductive Process

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6
Q

Begins with data collection, identifies patterns, and formulates a theory based on those patterns.

A

Inductive Process

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7
Q

an abstract concept that cannot be directly observed, such as ‘intelligence’ or ‘anxiety’.

A

theoretical construct

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8
Q

refers to the tools or methods used to observe these constructs, like surveys or behavioral assessments.

A

measure

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9
Q

how to turn a concept into something we can design and measure, informs study design

A

Operationalisation

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10
Q

Categorical variables without a meaningful order (e.g., gender, race).

A

Nominal Scale Variables

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11
Q

Variables with a meaningful order but no defined intervals (e.g., race finishing positions).

A

Ordinal Scale Variables

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12
Q

Variables with meaningful intervals but no true zero (e.g., temperature in Celsius).

A

Interval Scale Variables

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13
Q

Variables with a true zero, allowing for meaningful multiplication and division (e.g., weight).

A

Ratio Scale Variables

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14
Q

Consistency of a measure over time; repeated tests yield similar results.

A

Test-Retest Reliability

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15
Q

Consistency across different observers; different raters should produce similar results.

A

Inter-Rater Reliability

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16
Q

Consistency across different forms of a test; different versions should yield similar outcomes.

A

Parallel Forms Reliability

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17
Q

Consistency of results across items within a test; items should correlate well with each other.

A

Internal Consistency Reliability

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18
Q

The three core principles of human ethics in psychology

A

Respect/Autonomy, Beneficence, and Justice

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19
Q

in logical reasoning: if you ask people to decide whether a particular argument is logically valid (i.e., the conclusion would be true if the premises were true), we tend to be influenced by the believability of the conclusion, even when we shouldn’t

A

Belief Bias Effect

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20
Q

What do we want to know? How do we know what we know? What do we do with what we know?

A

Epistemology

21
Q

Systematic way to organise data, results, information to explain a phenomenon

22
Q

The process of how we test
predictions

23
Q

Does the measurement match up to the theory?- e.g. theory of the poll; these should be the options that people have when they vote

A

Construct Validity

24
Q

Is this the best design to answer the question?- can we trust what that thing says, e.g. giant meteor hitting the earth doesn’t reflect what they actually want

A

Internal Validity

25
Does it associate with the things it should in the world?- does it make sense with what we see in the world, e.g. Hillary Clinton did not win the election
External Validity
26
Participants respond in ways they think 1. the researcher wants/hypothesizes 2. that are acceptable or desirable under sociocultural norms
Demand Characteristics and Social Desirability
27
Dealing with Demand/Desirability
- “Double blind” measures, ensure confidentiality or anonymity wherever possible, emphasize there are no right or wrong answers - Check data for external validity with other sources - Use methodologies that counter (or capitalize on) demand/desirability characteristics
28
People tend to agree more commonly and more strongly than they tend to disagree
Acquiescence Bias
29
Dealing with Acquiescence Bias
- Use multiple items to average into one scale - Good reverse-wording avoids “not/never” Extroversion/Introversion “I talk to a lot...”/“I keep in the background” - Bonus: You can also remove the mid-point of the scale to avoid “neutrality bias”, but then be extra extra careful about acquiescence because people tend to agree. Or that they just get annoyed because they can’t answer how they want.
30
used to check consistency of our items that we want to average together into a scale
Cronbach’s Alpha test Above .70 = acceptable; above .80 = good; above .90 = excellent
31
Exposure to a question/answering a question influences answers and interpretation of subsequent questions
Priming “Affective priming” when answering questions about values, morals or attitudes (e.g., “good/bad”, ”love/hate”)
32
Dealing with Priming
- Move impactful questions to the end of the survey or have a “distraction task” in between scales - Randomize or counterbalance question order (this only averages the error across participants)
33
The extent to which your measurement is consistent
Reliability
34
Looks at people’s responses to the items and groups them to make the best summary of the items (the groups are called “components”)
Principal Components Analysis (PCA)
35
where you try different options in the data, method, or analysis, until you get a significant p-value
P-hacking
36
Planning and documenting the (1) hypothesis or research questions, (2) method, and (3) analyses before collecting data
Pre-Registration
37
hypothesising after the results are known- run a study, see the result, and then write the hypothesis, damaging to continuity (pattern identification & generalisation is moved to the wrong place), should have been reported as an exploratory finding
HARKing
38
Each person in a population has an equal chance of being chosen
Probability Sampling/Random Sampling
39
Divide the population into relevant groups, then randomly select people
Stratified Sampling
40
Specifically selected person/people
Purposive Sampling/Targeted Sampling
41
Whoever’s available
Convenience Sampling
42
concerned with reality and truth seeking e.g., what is existence, what is depression
Ontology
43
concerned with the nature of knowledge and the methods of learning e.g., what do you know, how do you know it
Epistemology
44
concerned with the method of data collection, Framework, how are you going to answer question e.g., empiricism, kaupapa Māori, interface research
methodology
45
describes how data was collected specifically, Tools, in what ways will you collect data e.g., surveys, interviews, experiments
methods
46
reality exists independently of the knowledge and experience of it- remove yourself, personal values/beliefs cannot and should not impact your perception of reality “third person perspective”
Objective Ontology
47
reality only exists when we experience it and give meaning to it- put yourself in, non-western approach, kaupapa maori, claims we cannot and should not extract ourselves from research, beliefs and values are important to how we analyse data “first person perspective”
Subjective Ontology
48
specific group, can produce knowledge that generalises but not specific goal, do not need lots of people to take part, more exploratory in nature, don’t necessarily make theories before starting, subjective, fluid method, guidelines rather than strict instructions, time-consuming
Qualitative
49
wider population, fixed method, quick, easier, less expensive
Quantitative