PSYC 70 Midterm 1--UCSD Geller

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psychological science

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91 Terms

1

psychological science

1. Systematic, iterative process of hypothesizing, predicting, and observing psychological phenomena with the intention of generating new knowledge
2. Process of learning about psychology in order to learn about our own human interactions.
3. Example: Every psychological experiment/research that has taken place!

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2

method of tenacity

clinging to beliefs & superstitions

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3

method of intuition

going on a hunch, common sense

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method of authority

consulting "experts"

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empirical method

observation through the senses

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which methods of knowing are most crucial for science?

rational & empirical methods

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7

variable

a quantity or quality that varies between individuals
can be quantitative (numerical) or qualitative (categorical)

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8

constructs

1. variables that can't be observed directly because they involve internal processes
2. things you can't assign a number or group to
examples: learning, intelligence level, emotional responses, etc.

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measurement

the process of assigning numbers or categories to the individuals in your sample

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operational definition

a definition of a variable or construct that specifies how it'll be measured in the study
example: measuring the love romantic partners have for each other through a self-reported survey

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correlation

a relationship between two quantitative variables
degree of relationship between two variables
ex: students who wrote by hand tended to score higher on their tests

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experiment

a design in which one variable is manipulated and extraneous variables are controlled, which allow us to make causal claims
ex: writing notes by hand caused students to do better on their tests

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phenomenon

a systematic observation
observed reliably in systematic empirical research
verified through replication

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theory

interpretation or explanation for phenomena
includes variables, processes, functions, etc. that haven't been organized directly
ex: drive theory. two phenomena of social inhibition and social facilitation explained by the single theory of drive theory.

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perspective

a broad approach to explaining/interpreting phenomena

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model

a precise explanation or interpretation in terms of equations, computer programs, or biological structures and processes

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formality

degree of clarity/specificity about components of a theory and how they relate to each other

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scope

number/scope of phenomena that a single theory can explain

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functional theoretical approach

focuses on the purpose of the phenomena

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mechanistic theoretical approach

focuses on variables, structures, processes, and how they interact

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typologies/stage theoretical approach

focusing on categorizing phenomena into types and stages

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the formula for a well formed hypothesis:

1. logical: follows from premises
2. testable: all variables can be directly observed
3. refutable: possible to disprove

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pseudoscience

hypotheses aren't refutable, no prior research, employs method of tenacity to the extreme

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construct

a theoretical variable that can't be observed directly
ex: emotions, cognitive processes, etc.

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conceptual construct definition

description of internal processes that are involved, along with how the construct relates to other variables

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operational construct

a definition of a variable of a construct in terms of how it'll be directly measured
ex. measuring levels of affection in a self reported survey

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self-report measures

a measure in which participants report their own thoughts, feelings, and behaviors

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behavioral measures

a measure in which the researcher observes and records some aspect of the participants' behavior

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physiological

a measure that involves recording a physiological variable

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ratio measurement

meaningful zero point
only important for ratio use (i.e. X is twice as ___ as Y)

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interval measurement

equal units
rare to find an interval that is also not a ratio
ex: Farenheit vs. Celsius; 0 has two different meanings on both scales

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ordinal measurement

ordered scores
calculating means would be inappropriate in this situation
ex: Likert scales of agree/disagree

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nominal measurement

category labels
binomial: 2 categories (heads/tails, yes/no, etc.)
multinomial: 3+ categories (favorite color, hometown, etc.)

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face validity

measurement seems to catch intended variable; catches the "sniff test"
common sense; does the test appear to test what it aims to test?

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content validity

covering all of the aspects of the construct being measured; covering all conceptual definitions of the construct

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construct validity

measurement behavior matches the variable, and reflects the behavior of past research

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concurrent validity

measurement correlates with a well established, valid measure of the same variable given at the same time

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convergent validity

measurement correlates with a measure of the same variable that is not well established

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divergent validity

measurement doesn't correlate with measure of some other variable we're not trying to measure

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predictive validity

measurement successfully predicts, according to some theory, a person's future behavior

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reliability

the extent to which scores on a measure are consistent:
1. over time
2. across multiple items
3. across observers

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measured value formula

measured value = true value + error

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observer error

measurement value dependent on who takes the measurement

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environmental error

measurement value dependent on the external conditions measurement was taken in

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participant error

measurement value dependent on current state of the person being measured

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test-retest reliability

reliability across time
ex: measuring a person multiple times and getting the same score; points to test reliability

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internal consistency

reliability across multiple items on the test
are scores for the specific test items consistent with each other?

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inter-rater reliability

reliability across observers
do different observers give the subject the same score?

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measurement artifacts

a non-natural feature introduced into an observation

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experimenter bias

a type of measurement artifact
experimenters' beliefs about a study can bias the observations

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participant reactivity

a type of measurement artifact
observing a participant influences participant behavior, according to demand characteristics

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blind study designs

purpose: eradicating measurement artifacts
participants (and sometimes experimenters) don't know what group/treatment they're in

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socially desirable responding

a type of participant reactivity
participants responding in ways that they believe to be socially desirable or acceptable

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demand characteristics

a study that cues participants as to how they're desirably expected to behave

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range effect

observers cluster at one end of a continuous measurement scale
1. ceiling effect: clustering at top of scale
2. floor effect: clustering at bottom of scale

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representative sample

closely mirrors the population of interest

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biased sample

differs in important characteristics of population, often due to sampling bias

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probability sampling

criteria met:
1. every individual in target population is identified
2. every individual has a certain probability of being selected
3. selection is random, based on probabilities of being selected

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nonprobability sampling

sampling in which one or more of the probability sampling criteria are not met

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simple random sampling

every member of the population target has an equal chance of being selected

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systematic sampling

over all individuals in the population, pick a random starting point, and then pick every nth individual

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cluster sampling

randomly select pre-existing groups, and measure all (or randomly sample) members of each group

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stratified random sampling

divide the population into subgroups, obtain equally sized random samples from each group

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proportionate stratified random sampling

divide population into subgroups, then pull random samples according to group population proportions

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non-probability sampling

applies when:
1. the population is not identified
2. the probability of selection cannot be calculated or is zero from some individuals
3. the selection process is not random

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convenience sampling

non-probability sampling
sampling those who are easily accessible (a lot of psyc research follows this model)

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quota sampling

non-probability sampling
selecting participants because they fit a specific category

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snowball sampling

non-probability sampling
participant suggests other people to participate (ex: drug addicts tend to know other drug users)

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purposive sampling

non-probability sampling
selecting participants because they are of theoretical interest

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the Law of Large Numbers

the larger the sample, the more representative it is of the population

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quantitative research

draws statistical conclusions
usually a small amount of data from a large pool of participants
interested in measuring variables and analyzing data using statistical techniques
good for testing hypothesis

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qualitative research

draws descriptive conclusions
usually a large amount of data from a small pool of participants
interested in synthesizing data through the "lived experience" (storytelling, direct interaction, etc.) to create a narrative
good for generating hypotheses

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73

grounded theory

an approach to analyzing qualitative data in which repeating ideas are identified and grouped into broader themes. themes integrated into a theoretical narrative

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theoretical narrative

a narrative interpretation that emerges from the data, usually supported by many direct quotations and examples

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internal validity

how are you sure that X causes Y?
-what if Y causes X instead?
-how do you know some other variable isn't causing both X & Y?

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the third variable problem

when some unidentified variable is responsible for the observed relationship between two variables

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the directionality problem

when two variables are related, it is unclear which variable effects/causes a change in the other.
-X--->Y?
-Y--->X?
-X<-->Y?

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independent variable (IV)

any variable that the researcher intentionally manipulates in order to cause the dependent variable

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dependent variable (DV)

any variable that the researcher measures as an outcome of the study. the effect of the independent variable

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extraneous variable

any variable in the context of the study that is not an IV or DV. may or may not be measured/controlled by the researcher

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confound variable

an extraneous variable that correlates with the independent variable and causes change in the dependent variable

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sources of confounds: environment

setting differs across most treatments

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sources of confounds: individual differences

assignment to treatment conditions results in groups with different characteristics

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sources of confounds: time

treatment conditions occur at different times and experience over time causes a change in the dependent variable

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history

time related confound
an outside event occurs between treatment conditions and affects DV subsequent to the event

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86

instrumentation

time related confound
change in measurement instruments between treatment conditions

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87

maturation

time related confound
subjects undergo natural physiological or psychological changes between treatment conditions

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mortality

time related confound
participants drop out of study

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89

order effect

time related confound
experience in first treatment condition causes change in subjects that affects performance in subsequent conditions

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predictor variable

variables in observational research; variables not manipulated; replacement for independent variable

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criterion variable

variables in observational research; variables not manipulated; replacement for independent variable

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