PSYC 70 Midterm 1--UCSD Geller

psychological science

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!

method of tenacity

clinging to beliefs & superstitions

method of intuition

going on a hunch, common sense

method of authority

consulting "experts"

empirical method

observation through the senses

which methods of knowing are most crucial for science?

rational & empirical methods

variable

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

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.

measurement

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

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

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

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

phenomenon

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

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.

perspective

a broad approach to explaining/interpreting phenomena

model

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

formality

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

scope

number/scope of phenomena that a single theory can explain

functional theoretical approach

focuses on the purpose of the phenomena

mechanistic theoretical approach

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

typologies/stage theoretical approach

focusing on categorizing phenomena into types and stages

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

pseudoscience

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

construct

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

conceptual construct definition

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

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

self-report measures

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

behavioral measures

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

physiological

a measure that involves recording a physiological variable

ratio measurement

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

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

ordinal measurement

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

nominal measurement

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

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?

content validity

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

construct validity

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

concurrent validity

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

convergent validity

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

divergent validity

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

predictive validity

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

reliability

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

measured value formula

measured value = true value + error

observer error

measurement value dependent on who takes the measurement

environmental error

measurement value dependent on the external conditions measurement was taken in

participant error

measurement value dependent on current state of the person being measured

test-retest reliability

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

internal consistency

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

inter-rater reliability

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

measurement artifacts

a non-natural feature introduced into an observation

experimenter bias

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

participant reactivity

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

blind study designs

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

socially desirable responding

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

demand characteristics

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

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

representative sample

closely mirrors the population of interest

biased sample

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

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

nonprobability sampling

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

simple random sampling

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

systematic sampling

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

cluster sampling

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

stratified random sampling

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

proportionate stratified random sampling

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

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

convenience sampling

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

quota sampling

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

snowball sampling

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

purposive sampling

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

the Law of Large Numbers

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

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

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

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

theoretical narrative

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

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?

the third variable problem

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

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?

independent variable (IV)

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

dependent variable (DV)

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

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

confound variable

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

sources of confounds: environment

setting differs across most treatments

sources of confounds: individual differences

assignment to treatment conditions results in groups with different characteristics

sources of confounds: time

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

history

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

instrumentation

time related confound
change in measurement instruments between treatment conditions

maturation

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

mortality

time related confound
participants drop out of study

order effect

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

predictor variable

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

criterion variable

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