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4 types of non-data driven bases of information

experience, common sense, authority, intuition (logic)

intuition

unquestioning acceptance of own judgement (gut feeling)

pros of intuition

easy to access knowledge and quickly

allows us to understand values that are important to us

cons of intuition

humans are not rational beings. we rely on emotions and connections to fuel our decision-making which may be biased. opaque, easy to see through, no one knows where the information came from, they don't know how you're wrong or right, subject to prejudices and misconceptions

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difficult to analyze and critique

subject to prejudices and misconceptions

authority

knowledge based on a credible other i.e. outsourced learning from a credible person e.g. Jennifer Aniston drinks smart water, therefore it must make you awesome like her. she knows more about water than you do

pros of authority

minimises the need to acquire knowledge on your own

many people have legitimate credentials to be considered authority

someone has more experience than you and may actually make more informed decisions in their field. probably a good source of information but not DATA-DRIVEN

cons of authority

may be wrong

authorities can base their info on things like intuition or fold wisdom

authority figure may be caused by perceived sense of credibility (attractiveness, well spoken, popularity)

common sense

appeals to what everyone should know e.g. popular cultural sayings

pros of common sense

there is an explanation for every situation

short, mutually understood ways of communicating a more complex idea.

cons of common sense

often contradictory, rendering them meaningless

cannot be refuted or falsified

logic

pros: internally consistent reasoning, easy to analyze and critique

cons: based on incorrect premises, logically consistent differs from what occurs in the world

determinisim

the assumption that the universe is orderly, things are not completely random because if they are, theres no point in research, events occur due to some meaningful and systematic cause (determined by), foundation of research

four canons of science

determinism, empiricism, parsimony, testability

empiricism

we dont just make assumptions and draw conclusions based on those assumptions,

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we make structured systematic observations and account for other explanations

parismony

when two theories are equally able to explain the same set of findings, we opt for the idea that is simpler, occams razor, make the least amount of assumptions possible

logic

obtaining knowledge based on a series of steps or thinking processes, non-data driven, but part of scientific method

social science brief

Brown vs. board of education, supreme court case that banned segregation in schools. cited a study in which both black and white children chose to play with white dolls, both children viewed white dolls as superior

illusory correlation

occurs when we focus on two events that stand out and occur together-->biased to conclude two events are related, especially when highly motivated to believe both are related

falsifiable

can be supported or refuted with empirical data i.e. Freud's ideas fell away b/c they are not falsifiable

pseudoscience

using scientific terms to substantiate claims without using scientific data, but no evidence to back up their claims i.e. proactiv- cures 100% of acne ALL the time!

3 ways to determine cause of a behavior

covariation of cause and effect-cause is present, then effect occurs AND when cause is not present, effect does NOT occur, temporal precedence-cause occurs BEFORE the effect, alternative explanation elimination (no other plausible explanation for the relationship)

basic research

attempts to answer fundamental questions about the nature of behavior (Skinner operant conditioning)

applied research

conducted to address practical problems and potential solutions

testability

ability for the theory to undergo a scientific test and be falsifiable

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researchers should be able to put a theory to empirical tests

induction

observe something in the environment, create a hypothesis and if it is supported, it can be a theory

deduction

realize overarching framework that organizes and explains data and phenomena, generate hypothesis and create and prediction about the study

induction arrows

observation-->hypothesis-->theory I often hide timely

deduction arrows

theory-->hypothesis-->prediction

abduction

specific observation > trying to determine best explanation for single observation; no involvement of theory

absence of a theory, used to be called guessing. observation, try to figure out what happened to cause this. only see the result, trying to find causation i.e. doctors diagnosing patients knowing only their symptoms. observation-->causation act old, cole

Loftus study

asking about a car accident, participants answered differently based on how they were questioned. "did you see 'the' broken tail light?" vs. 'a' broken tail light. proved memories are easily reconstructed and configured by oral manipulation.

facilitated communication

tested by Montee et al. facilitator was actually helping the autistic kid answer the questions correctly

essentialism

unchanging, underlying essence of an entity that can be defined, sense of fixedness, focus is on the meaning of words i.e. aggression caused by video games

Eagly and Wood study

sex differences arise from historic male-female division of labour

\-men support financially

\-women care for children

Young et al. study

females on calorie consumption-ate less when eating with males and females as opposed to just females.

operationism

observable indicator of each variable, used for the purposes of the particular study. enable reliable measurements or manipulation of each variable in your hypothesis. i.e. conceptual variable: aggression --> operational definition: whether they punish their partner by blasting in ears after end of the game

operational definition for violent video games

frequency of playing games X rating of a game's violence

operational definition for aggression

self-report hostility scale

Douglas Gentille study

studied the effects of video games on behavior in children

bi-directionality problem

cause could spur the effect or the cause could exist because of the effect. lacks temporal precedence--> the way in which the causation relationship progresses

issues with correlational studies

low internal validity, cannot infer causal relationships

most common measure

self-report

3 things required to create internal validity (to identify CAUSE of behavior)

covariation between variables, both variables are related. children who watch violent video games are violent, children who do not, are not. temporal precedence-watching the video games occurred first, aggression followed. eliminate alternative causal explanations, experimental control, and random assignment

demand characteristics

something in the study that gives away the hypothesis or staging of the study. threaten to internal validity. participants might try to help or hinder the study

Hawthorne effect

participants act differently because they know they're being observed

evaluation apprehension

i.e. stereotype threat: concerned about confirming their own stereotype-->could end up confirming it by trying to avoid it. test anxiety

manipulation check

additional set of dependent variables that have to do with what are people's perception of the manipulation? does it match with the researchers intent? i.e. people didn't think that the violent video game was actually violent

quantitative data

all statistical and based on analysis of numbers. self-report measures

behavioral data

recording or coding someones behavior. how aggressive does the person look or body language to code their behavior into numbers. how quickly is the person running?

types of measures

self-report

behavioral

physiological

biological data

heart rate, BP, respiration rate, blood sample, changes in hormones in response to stimuli

semantic differential scale

sad-happy complete opposites

Likert scale

numbered, how much pain are you in? scale of 1 to 10

forced choice

i.e. how many times have you lied? eliminate the option of zero

outcome variables

self report, behavior responses, physiological responses

Hawthorne effect

participants act differently because they know they're being studied

how to avoid demand characteristics

blind studies, filler/distractor items, vague wording, deception

biosocial effect

perceived biological nature of experimenter effects participant behavior i.e. black experimenter might make researcher uncomfortable

psychological efect

behavior of experimenter effects participant behavior i.e experimenter smiles a lot

immersive effect

very violent and graphic video game to make you feel more like its real. study that completely immerses participant in the situation in order to illicit a particular response

semantic differential scale

opposite anchors at each end of the scale. how do you feel? bored...excited

how to counteract yea or nay saying?

have two counteractive questions with different answers for the same response. do you think everyone should be free to own a gun? AND we need to have strict gun control?

between subject design

large sample size, only exposed to one condition

within subject design

participants are exposed to all conditions

types of between subject designs

pretest and posttest or just posttest

within subject measures

concurrent measures design and repeated measures design

how do we ask questions

open ended (asking question in a way that allows participant to elaborate on whatever they want)

close ended (participants are limited to what the researchers want)

likert scales

anchors (labels) like not at all to extremely

numbers from 1-5

likert-type scales

anchors and numbers but can be different in labels or number range

semantic differential scale

two options

non-verbal scale

using a scale without words

forced choice questions

could be open-ended but response are limited to a set of pre-set responses to choose from

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easy for data collection and analysis

yay-saying

agreeing with everything in response to questions

nay-saying

disagreeing with everything in response to questions

fence-sitting

being neutral always in response to questions

repeated measures design

participants exposed to all conditions and dv measured after each exposure

concurrent measures design

dv measured at end

concurrent measures issues

restricted in what research questions we can ask

strong demand characteristics

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problems with repeated-measures design

demand characteristics

carryover effects

types of order effects

fatigue

practice

contrast

order effects

participant’s response in one condition is affected by having been in another condition

another term for order effects

carryover effects

how to deal with order effects

switching up the order of conditions

latin squares

pros of concurrent design

quick to administer and run

pros of repeated measure

serve as own control

requires fewer participants

observed score is made up of

true ability + error

error

sources of variability in measurement caught by things other than measurement of iv

two components of errors

random, systematic

ways of knowing (unscientific)

experience

folk wisdom/common sense

authority

intuition

ways of knowing (scientific)

logic

experience

relying on personal experience to make decisions

experience pros

may be representative of collection of all possible experiences

vivid examples that are easy to remember

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experience cons

may not be representative of collection of all possible experiences

cannot account for alternative explanations

determinism

the assumption that the universe is orderly

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idea that things don't completely happen at random, there are predictable, meaningful

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systematic causes that lead to certain behaviors

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foundation

theory

overarching framework that encapsulates phenomenon and data collected

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generates hypothesis that test boundaries of the theory

hypothesis

a tentative statement that may not be about a relationship that may or may not be true

prediction

specific statement regarding the expected outcome of a study

bushman and gibson

video game study where participants play video games with a partner and have the option to punish partner for losing with a white noise blasted in headphone

internal validity

ability to infer that one variable causes change in another variable

3 criteria for establishing causality

temporal precedence (establishing cause before effect)

covariation between two variables (2 variables changing w each other)

eliminating plausible alt explanations