4 systems of history of human knowledge
metaphysical, philosophy, physiology, experimental psychology
Explain metaphysical systems
supernatural
non scientific
animism- belief that non living things have life-like qualities (not scientific)
mythology and religion- behavior based on Gods/goddess (not scientific)
astrology- info based on planets (horoscope)(a little scientific)
what is animism
belief that non living things have life-like qualities (not scientific)
Explain philosophy
more scientific than metaphysical asks the questions plato- importance of nature aristotle- importance of nurture used to be more speculation, now more experimental dacarte- one of 1st empiricism
Explain physiology
answers the questions
study how things function in the body (biology)
gather data, test hypothesis
Galvani- biologist studied frogs
Explain Experimental psychology
schools of thought (ways of thinking)
founded in Germany by Wundt
study consciousness
What two sciences is psychology based on?
philosophy and physiology
What are the 4 cannons of science?
determinism, empiricism, parsimony, testability
explain determinism (example)
universe is orderly
cause and effect
everything happens for a reason
Key is: is attitude going to predict behavior?
Illusory correlation (we perceive correlation between things but there’s actually no relationship) (ex. Lucky jersey)
**False conditioning of random behaviors = superstitions
Ex. Skinner’s (behaviorist) superstitions conditioning, pigeon experiment, operant conditioning (rewards/ punishment)
what is Illusory correlation
we perceive correlation between things but there’s actually no relationship (ex. if you wash your car, it is going to rain) superstition
explain Empiricism (example)
observe behavior
Ex. the phrase talk is cheap, go out and do ti
explain parsimony
something simple/ easily explained
boxology- organized info, but its not simple. it has a lot of boxes
explain testability
we test hypotheses not theories
theories lead to hypotheses
falsifiability
define theory (example)
statement about the relationship between 2 things
Ex. relationship between marriage and happiness
define hypothesis (example)
testable prediction
Ex. married people are happier than single people
define operational definitions (example)
concept defined in terms of how its measured
more concrete
Ex. Define Love, Operational definition= the number of times a couple says “i love you” in one day
define conceptual definitions (example)
more dictionary definition
cant really be measured
Ex. Define Love, Conceptual definition= deep affection and fondness of someone
ways of knowing
intuition- emotional reasoning, not scientific
tenacity- determined, accept information as true if we hear it repeated (dont swallow gum)
reason and logic- not scientific
authority- not scientific
observation- scientific, mostly indirect (empiricism)
goals of behavioral research
describe behavior
understand behavior
predicting behavior
solve applied problems
Occam’s Razor & Lloyd Morgan’s Canon – pp.16-17
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difference between law, theory, and hypothesis
a law is a UNIVERSAL statement of the nature of things that allows reliable predictions of future events (comprehensive)
a theory is a GENERAL statement about the relationship between 2 or more variables (boundary conditions and equifinality)
a hypothesis is a testable prediction
what makes a theory good?
simple and useful
boundary conditions
times when they don’t apply (ex. frustration leads to aggression)
Equifinality
human behavior usually has multiple determinants (ex. depression)
approaches to hypothesis testing
- validation- most common, gather evidence that confirms hypothesis (positive test bias)
- falsification- gathers evidence that disconfirms hypothesis
- qualification- identify boundary conditions
positive test bias
tendency to confirm rather than disconfirm
behavioral confirmation
tendency to search for info that confirms our preconceptions
inductive techniques of generating a hypothesis
reasoning from specific to general
observational (systematic empiricism)
Ex. experiment, case study, paradoxical incidents, serendipity
Paradoxical: puzzling behavior, doesn’t really make sense, draws more general conclusions
Serendipity: good luck/fortune. Lead you to more general conclusion
Skinner: behavioral psychologist did research on animals and studied behavior, Partial Reinforcement effect- study behavior and study continual reinforcement
hypothesis to a theory
deductive techniques of generating a hypothesis
Reasoning from general to specific
Reasoning by analogy (ex. McGuire’s attitude inoculation) (comparison of people, places, things, events)
McGuire social psychologist who studied attitudes.
Attitude inoculation- pulls something biological and connects it to attitude. If exposed to small weaker argument, and later exposed to big argument
Accounting for conflicting results
Example: Theory to a hypothesis
IRB institutional review board
college human subject committee
at least 5 members
varying background
at least one member not affiliated with institution
Risk benefit ratio
Subjective evaluation of the costs to the individual/ society vs. costs of not conducting the research
is it worth it?
minimal risk vs risk (example)
Minimal Risk: risk not above daily activity (ex. Walking to class, driving)
At Risk: potential of injury above that involved in daily activity (ex. Skydiving, driving blindfolded)
Human Guidelines:
Informed consent (willingness to participate)
Confidentiality
Freedom to withdraw
Protection from harm (physical and psychological)
Deception
Debriefing
Fudging data:
(least bad) manipulate results to make it look better
Forging data:
(worse) completely make up data
Types of Measurement:
Behavioral
Physiological
Self-report
Converging Measures
measurement scales
nominal, ordinal, interval & ratio
nominal
Arbitrary # assignment, numbers simply differentiates between objects
No limit
Weakest level
Ex. Baseball uniform numbers
ordinal
Assign numbers to objects but the numbers also have meaningful order
Number indicated placement, rank, or order
Behaviors or individuals on some dimension
Can’t quantify differences between categories
Stronger level
Ex. Place finished in race: 1st, 2nd, 3rd
interval
Number’s make order (like ordinal) but there also equal intervals between categories
Difference represent equal increments (intervals)
Not a true zero
Stronger level
Ex. Temperature
ratio
Differences are meaningful (like interval) plus ratios are meaningful Provides the most info Ordering of scores Equal intervals True zero Physical attributes of objects Ex. Weight
categorical versus continuous variables
categorical- values that function as labels rather than numbers
ex: gender, race
continuous- numeric value such as 1,2,3
ex: BP, HR, height
internal validity
confident x caused y
covariation- related variables
temporal sequence- directionality
eliminate confounds- can control confound systematically changes with independent variables
random assignment- within the study, everyone has an equal chance of being assigned
external validity
generalizability
can i apply findings to a larger population?
two forms: to people and to situation
random sample- everyone at sdsu has an equal change of being picked
reliability
consistency or repeatability
observed score = true score + measurement error
90 = 95 + sick
causes of measurement error
state of subject; stable characteristics of subject; situational factors; characteristics of measure; mistakes recording responses
interrrater reliability
2 researchers observing/ recording behavior
calculate- number of times 2 observers agree/ number of oppurtunities to agree x 100
need atleast 85%
data at least interval - correlation
need atleast .70
test- retest reliabilty
at least .70
ex: IQ test today is the same in 1 month
how to increase reliability?
instructions; train observers
descriptive statistics
used to summarize or describe a set of observation
ex: frequency distribution, graphs
central tendency
representatice number that characterizes the middleness of an entire data set
ex: mean, median, mode
dispersion (variability)
degree to which the scores are clustered or spread in distribution
ex: range, variance, sd
total variance = systematic variance and error variance
systematic variance/total variance = effect size (sm, med, lg)
inferential
used to interpret or draw frequencies about a set of observation
ex: chi- square, correlation, t- test
The intuition that machines (e.g., computers or cars) have temperaments or desires reflects _____ thinking.
Answer: Animistic
Phenomena such as the illusory correlation and superstitious conditioning are consistent with the basic idea behind _____.
Answer: Determinism
The principle of ____ refers to the idea that the same behavior is often produced by many different causes.
Answer: Equifinality
Induction refers to reasoning _______.
Answer: From the specific to the general
Studies that provide good information about causal relations between variables are high in _____.
Answer: Internal Validity