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PYSC 100 > PSYC 100 Chapter 2 > Flashcards

PSYC 100 Chapter 2 Flashcards

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1
Q

scientific method

A

The process of basing one’s confidence in an idea on systematic, direct observations of the world, usually by setting up research studies to test ideas

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2
Q

theory-data cycle

A

The process of the scientific method, in which scientists collect data that can either confirm or disconfirm a theory.

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3
Q

theory

A

A set of propositions explaining how and why people act, think or feel.

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4
Q

hypothesis

A

A specific prediction stating what will happen in a study if the theory is correct

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5
Q

Data

A

A set of empirical observations that scientists have gathered.

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6
Q

replication

A

When a study is conducted more than once on a new sample of participants, and obtains the same basic results.

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7
Q

journal

A

A periodical containing peer-reviewed articles on a specific academic discipline, written for a scholarly audience

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8
Q

variable

A

Something of interest that varies from person to person or situation to situation

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9
Q

measured variable

A

A variable whose values are simply recorded

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10
Q

manipulated variable

A

A variable whose values the researcher controls, usually by assigning different participants to different levels of that variable

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11
Q

internal validity

A

ability to infer causal relationships

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12
Q

external validity

A

ability to find the same result in the real world

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13
Q

Naturalistic observation

A

Observing real behavior without trying to actively manipulate what
is going on

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14
Q

Naturalistic observation

A

Observing real behavior without trying to actively manipulate what
is going on
High in External Validity
Low in Internal Validity

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15
Q

Case Study

A

Examining a small number of people in a very detailed way, tells nothing about its prevalence in the whole population

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16
Q

Existence proof

A

one example of a psychological phenomenon

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17
Q

Self-report measures & Surveys

A

usually used to assess things that are only available to the people themselves
-Easy and inexpensive to use
-Works well enough to be used for some traits
-Not all people may have enough insight into themselves to successfully
report traits
-May result in response sets (distortions in answering questions)

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18
Q

Random Selection

A

every person in a population has an equal chance to be in a poll
(can be better than large non-randomized sample)

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19
Q

Reliability

A

whether or not a measurement is consistent across different factors

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20
Q

Test-retest reliability

A

is the test the same if you give it again?

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21
Q

Interrater reliability

A

do different people agree on what they are rating?

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22
Q

validity

A

whether a measurement
actually assesses what it should

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23
Q

Rating others (pros and cons)

A

-Rating others may avoid blind spots in our own performance
-Susceptible to the halo effect – one positive trait can make other traits
seem more positive
-Horns effect – disliking a person can blind you to their positive trait

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24
Q

Correlational Design

A

a research design that investigates the
association between two variables

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25
Positive Correlation
as one variable increases, another variable also increases
26
Negative correlation
as one variable increases, another variable decreases
27
No correlation
No relationship exists between two variables
28
Correlation is not equal to...
Causation
29
experiment
A design where participants are randomly assigned to conditions that manipulate an independent variable
30
Random Assignment
participants have an equal chance of ending up in any condition
31
Experimental group
the group that is manipulated by the experimenter
32
Control group
the group who is not manipulated
33
Independent Variable
the variable that is changed by the experimenter
34
Dependent Variable
the variable that is measured; is expected to change in response to the independent variable
35
Operational definition
a “working” definition of what an experimenter is measuring
36
Confounding variable
an additional difference between the experimental and control groups
37
Placebo effect
participants show improvement because it is expected
38
Nocebo effect
participants show harm because it is expected
39
Blind
awareness of who is in the control group
40
Experimenter Expectancy Effect
the hypothesis of a researcher leads to unintentionally biasing an outcome
41
Double-blind
neither researchers nor participants know who is in what group
42
demand characteristics
when participants act in a way that reflects what they think the experimenter wants
43
descriptive formulas
the mathematical formulas that we use to describe a single variable
44
third-variable problem
For a given observed relationship between two variables, an additional variable that is associated with both of them, making the additional variable an alternative explanation for the observed relationship
45
confound
An alternative explanation for a relationship between two variables; specifically, in an experiment, when two experimental groups accidentally differ on more than just the independent variable, which causes a problem for internal validity
46
Central tendency
ways of measuring the most common cluster of scores in a data set
47
Mean
or average is the sum of all the data points divided by the number of data points
48
Median
when all data points are ordered, the number in the middle
49
Mode
the most common value of data point
50
variability
or dispersion, tells us how loosely or tightly packed the data is
51
range
the difference between the highest and lowest values of this variable
52
standard deviation
a measure of how far each data point is from the mean
53
Effect size
A numerical estimate of the strength of the relationship between two variables. It can take the form of a correlation coefficient or, for an experiment, the difference between two groups (with some calculations).
54
Inferential statistics
to decide whether or not a sample's results can be applied to make conclusions about an entire population
55
Statistical significance level
the probability of finding such an [experimental groups mean difference] by chance
56
Base rate fallacy
ignoring the overall likelihood of an event when measuring
57
Informed consent
participants know they are in a study, and know what risks are involved
58
meta-analysis
A process in which researchers locate all of the studies that have tested the same variables and mathematically average them to estimate the effect size of the entire body of studies.
59
IRB approval
an institutional review board must approve the study
60
Debriefing
Participants must be informed of what happened in full after the experiment
61
Standards to be considered an ethical study
IRB approval, Debriefing, Informed consent, Scientific knowledge outweighs harm
62
false positive
A statistically significant finding that does not reflect a real effect.
63
HARKing
making a hypothesis after you know the results
64
p-hacking
questionable data analysis techniques
65
open science
the practice of sharing one’s data, hypotheses, and materials freely so others can collaborate, use, and verify the results.
66
preregistration
A researcher’s public statement of a study’s expected outcome before collecting any data.
67
scientific method
theory, hypothesis, design, collect data, compare

PYSC 100 (11 decks)

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