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PYSC 100 > PSYC 100 Chapter 2 > Flashcards

PSYC 100 Chapter 2 Flashcards

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
Q

Positive Correlation

A

as one variable increases, another
variable also increases

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26
Q

Negative correlation

A

as one variable increases, another
variable decreases

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27
Q

No correlation

A

No relationship exists between two variables

28
Q

Correlation is not equal to…

A

Causation

29
Q

experiment

A

A design where participants are randomly assigned to conditions that manipulate an independent variable

30
Q

Random Assignment

A

participants have an equal chance of
ending up in any condition

31
Q

Experimental group

A

the group that is manipulated by the
experimenter

32
Q

Control group

A

the group who is not manipulated

33
Q

Independent Variable

A

the variable that is changed by the experimenter

34
Q

Dependent Variable

A

the variable that is measured; is expected to change in response to the independent variable

35
Q

Operational definition

A

a “working” definition of what an experimenter is measuring

36
Q

Confounding variable

A

an additional difference between the experimental and control groups

37
Q

Placebo effect

A

participants show improvement because it is expected

38
Q

Nocebo effect

A

participants show harm because it is expected

39
Q

Blind

A

awareness of who is in the control group

40
Q

Experimenter Expectancy Effect

A

the hypothesis of a researcher leads to
unintentionally biasing an outcome

41
Q

Double-blind

A

neither researchers nor participants know who is in what group

42
Q

demand characteristics

A

when participants act in a way that reflects what they think the experimenter wants

43
Q

descriptive formulas

A

the mathematical formulas that we use to describe a single variable

44
Q

third-variable problem

A

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
Q

confound

A

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
Q

Central tendency

A

ways of measuring the most common cluster of scores in a data set

47
Q

Mean

A

or average is the sum of all the data points divided by the number of data points

48
Q

Median

A

when all data points are ordered, the number in the middle

49
Q

Mode

A

the most common value of data point

50
Q

variability

A

or dispersion, tells us how loosely or tightly packed the data is

51
Q

range

A

the difference between the highest and lowest values of this variable

52
Q

standard deviation

A

a measure of how far each data point is from the mean

53
Q

Effect size

A

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
Q

Inferential statistics

A

to decide whether or not a sample’s results can be applied to make conclusions about an entire population

55
Q

Statistical significance level

A

the probability of finding such an [experimental groups mean difference] by chance

56
Q

Base rate fallacy

A

ignoring the overall likelihood of an event when measuring

57
Q

Informed consent

A

participants know they are in a study, and know what risks are involved

58
Q

meta-analysis

A

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
Q

IRB approval

A

an institutional review board must approve the study

60
Q

Debriefing

A

Participants must be informed of what happened in full after the experiment

61
Q

Standards to be considered an ethical study

A

IRB approval, Debriefing, Informed consent, Scientific knowledge outweighs harm

62
Q

false positive

A

A statistically significant finding that does not reflect a real effect.

63
Q

HARKing

A

making a hypothesis after you know the results

64
Q

p-hacking

A

questionable data analysis techniques

65
Q

open science

A

the practice of sharing one’s data, hypotheses, and materials freely so others can collaborate, use, and verify the results.

66
Q

preregistration

A

A researcher’s public statement of a study’s expected outcome before collecting any data.

67
Q

scientific method

A

theory, hypothesis, design, collect data, compare

PYSC 100 (11 decks)

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