ap psych test unit 2 m4-m8 10/10/23

fyi trhis is like not in order of the modules or anything lol t's just mushing the hw and class nores together

statistics

statistics

tools that help us see and interpret what the unaided eye might miss-turn data into information

descriptive statistics

used to describe the sample being studied, organizes data

proxy

something that is related to what we want to measure, but not exactly

measures of central tendency (definition)

single value that represents a whole set of values

mode

most frequently occurring value-simplest measure

median/arithmetic average

total sum of all values divided by number of values; skewed by outliers

median

midpoint/50th percentile

measures of variation

how similar or diverse the values are; averages from values with low variability are more reliable

range

gap between the lowest and highest values; can be deceptively large because of extreme values

standard deviation

how much the values differ from the mean

z-score

assesses a specific value's distance from the mean

the normal curve

68% of cases fall within 1 SD, 95% of cases fall within 2 SD, 99% of cases fall within 3 SD; often forms with large numbers of data and representative samples

inferential statistics

can results be generalized to a larger population from a smaller sample

inferential errors

anything that encourages us to link a small group to a larger group where a link shouldn't exist

a difference is statistically significant when

averages from two samples are each reliable measures of their populations (many observations with low variability) and the difference between them is likely to be large and not due to chance variation between the samples

null hypothesis

predicts there will not be a significant relationship; results cannot be applied to a larger population; goal is to disprove it

Type I/false alarm error

expected significant, results not significant

Type II/false negative error

expected insignificant, results significant

perception varies depending on

personality traits

intuition

using past experience to help you make a decision; unreliable

confirmation bias

people don't consider data that don't support their own conclusions

correlation

one trait or behavior is related to another, shown by naturalistic observations and surveys; can be revealed by scatterplots

correlation coefficient

how closely two things vary together/how well either one predicts the other; ranges from perfect positive to perfect negative

correlations aid

predictions; if something correlates with something else, only indicates the possibility of causation

illusory correlations

perceived but nonexistent correlations; when we believe there is a relationship between two things, we are likely to notice and recall instances that confirm our belief (superstitions, weird coincidences)

experimental research method (i.e. describe what an experiment is lolz)

used to isolate cause and effect by manipulating variables of interest to determine effect while holding others constant (experimental and control groups)

minimize differences between the two groups (experimental and control) with

random sampling and assigment

double-blind procedure

neither the participants nor research assistant know which group receives the treatment

placebo effect

just thinking you are getting a treatment can help you recover

independent variable

variable that is being manipulated

confounding variables

factors that can potentially influence the experiment's results, controlled for by random assignment; interacts with the DV and makes the IV extremely effective or ineffective

dependent variable

measurable behavior that is affected by the independent variable

extraneous variables

factors that seem likely to influence the DV in a specific study

validity in experimental design

experiment tests what it is supposed to test

hindsight bias

“i knew it all along”-when things seem like common sense

overconfidence

we tend to think we know more than we do; when wrong, we say we were close or almost right

rage for order

we are prone to perceive patterns and randomness often doesn’t look random; patterns and streaks occur more often than expected

with a large enough sample

any unlikely event can happen

empirical approach

“proof is in the pudding”-no matter how sensible or wild an idea sounds, can we confirm its predictions?

curious skepticism

passion to explore and understand without misleadership and by being doubtful

humility

opinions don’t matter, only the truth revealed by nature

critical thinking

examines assumptions, assesses the source, discerns hidden values, confirms evidence, and assesses conclusions; questioning credibility, considers other perspectives, challenges preconceptions

scientific method

self correcting process for evaluating ideas with observation and analysis, testing theories

theory

explains behaviors or events by offering ideas that organize and summarize observations; can bias our observations

hypotheses

testable predictions produced by theories; what results would support/not support the theory

operational definitions

describe concepts with precise procedures or measures to allow for research replication with different participants and situations

descriptive research methods

describe behaviors, often through case studies, surveys, or naturalistic observations

correlational research methods

associate different variables (anything that contributes to a result in research)

experimental methods

manipulate variables to discover their effects

case study

analysis of a specific special individual in hopes of revealing something true of all of us

naturalistic observation

watching and recording many individuals’ natural behavior without intervening directly; often practiced on animals

surveys/interviews

asking people questions; many cases in less depth to estimate about a whole population based on a representative sample

sampling bias

we tend to generalize from samples we observe, especially vivid and biased ones

random sampling

everyone has an equal chance of participating

stratified sampling

dividing target population into important subcategories-selecting members in proportion that they occur in the population

volunteer sampling

self-selecting individuals who have chosen to be involved in a study; unrepresentative because of participant's bias

opportunity sampling

selecting people that are readily available; unrepresentative because of researchers’ bias in choosing who seems helpful

in choosing a group that would represent the total population

larger sample size is better, unless there is a smaller one that would be more representative (cannot compensate for an unrepresentative sample by just adding more people)

belmont report

ethical principles for human research-respect for persons (informed consent), beneficience (don't have negative impact on participants), justice (prevent exploitation)

likert scale

rating scale that quantitatively assesses opinions, attitudes, or behaviors

meta-analysis

looking at other doctor's data and combine it to make an analysis

longitudinal study

shows changes over time/developmental analysis

cross-sectional study

examines differences between participants of different ages at the same point at time

false consensus effect

tendency to overestimate how much others share our beliefs and behaviors

observer effect

making sure the observer doesn't have an affect on the subject being observed

participation observation

observing a group by blending in

observer bias

only recording observations that support observer's views

ex-post facto study

studying something after it happened naturally; looking at the effect to seek the cause

replication

repeating the essence of a research study, usually with different participants and situations, to see if the basic finding can be generalized