AP Psych Unit 0 (L)

the nature-nurture controversy

controversy over whether human traits and behaviors are based on biology (nature) or one's environment/experiences (nurture)

quantitative methods

objective observations of human behavior quantified into widely recognized (or even standardized) units

qualitative methods

observations of human behavior that use in-depth, narrative data

developmental

studies how behavior & mental processes change over lifespan

cognitive

studies how we perceive, think and solve problems

personality

Unique attitudes, behaviors, and emotions that characterize a person

counseling

helps people cope with academic, vocational and marital challenges (among other issues)

clinical

studies, assesses and treats people that are experiencing psychological disorders

environmental

study how individuals interact with their natural and urban environments (e.g., study the impact of urbanization on human health)

rehabilitation

help individuals who lose optimal functioning after an accident, illness or other event; also aid individuals with physical disabilities

clinical psychologist

holder of Ph.D.; in the US, typically a member of the APA (American Psychological Association); studies, assesses and treats troubled people, typically with therapies like CBT (cognitive-behavioral therapy) or psychotherapy

psychiatrist

licensed medical professional (M.D.); uses treatments including drugs and psychotherapy to treat psychologically diseased patients

pseudoscience

a system of theories, assumptions and methods erroneously regarded as scientific

variable

a psychological or behavior measurement that changes (either over time or from participant to participant)

theory

an explanation that integrates principles, organizes and predicts behaviors or events

hypothesis

a testable prediction, often induced by a theory, to enable us to accept, reject or revise the theory we are examining

hindsight bias

the tendency for a researcher to believe, after learning an outcome, that he/she would have foreseen it

the experimenter effect (the pygmalion effect)

the tendency for a researcher act in a way that conforms to their expectations of the results and unexpectedly impacts the outcome of the experiment (either through interaction with participants or unintentional errors of observation)

overconfidence

the tendency for individuals to have great certainty of their knowledge of a situation (or the results of a event) before the results have been revealed

confirmation bias

the tendency for the researcher to look for information that confirms his/her beliefs and ignore all other evidence that may disprove it

peer-reviewed research

when scientific experts (i.e., peer reviewers) evaluate a research article's theory, originality and accuracy to determine if it should be published or not

perceiving order in randomness

the tendency for individuals to believe that certain rules or guiding principles exist in their environment when in reality their environment does not follow those rules or guiding principles

illusory correlation

perceiving a relationship where none exists (or perceiving a stronger-than-actual relationship)

regression toward the mean

the tendency for extreme or unusual scores or events to fall back (regress) toward the average

APA

American Psychological Association

IRB (institutional review board)

the panel that judges the ethical standards of a project and decides whether it can be approved

informed consent

must inform potential participants about every aspect of the study that might influence their decision to participate and ensure that participation is voluntary

limited deception

must ONLY deceive people when it is absolutely essential to the study and MUST tell about deception at end of study during debriefing (i.e., deception must be justified)

protection from harm and discomfort

must minimize any discomfort or risk involved in the study and must act to prevent participants from suffering any long-term negative consequences

confidentiality

must keep personal information about the participants a secret…report results in such a way that personal information is not disclosed

debriefing

must reveal all relevant information about the research and correcting any misimpressions it created; participant must leave the study in the same way they arrived

descriptive studies

studies that attempt to describe behavior through directly observing subjects (no manipulation); includes case studies, surveys and naturalistic observations

correlational studies

studies that attempt to find associations (i.e., bidirectional relationships) between different variables; includes studies that use surveys or tests

experimental studies

studies that attempt to find causal relationships (i.e., one-way causal relationships) between different variables; needs to manipulate IV and measure changes in DV

naturalistic observation

observe people in their natural environments (or in a laboratory without manipulating variables); gather descriptive information about typical behavior of people or animals without manipulating any variables

case study

In-depth examination of a specific group or single person in the hope of revealing universal principles; Useful for understanding rare or complex phenomena

survey

used to ask a large number of people questions about their thoughts, attitudes, emotions and behaviors

cross-sectional study

research that compares people of different ages at the same point in time; no causal claims (i.e., does not prove a cause-and-effect relationship)

longitudinal study

research that follows and retests the same people over time; better causal claims (b/c measures changes of variable A at time 1 and changes of variable B at time 2; still some issues with confounding variables)

wording effects

the way a statement in a survey is worded influencing the way people answer that survey item

social desirability

the tendency for people to answer survey items in a way that makes them appear to fit social norms (i.e., social conventions)

adjacent questions

preceding items in a survey may affect how people answer subsequent items (particularly those that immediately follow)

random sample

a sample that theoretically represents a population well because each member has an equal chance of inclusion (we want our findings to be generalizable)

stratified sample

population is divided into relevant subcategories and a random sample is taken from each subcategory

population

all the individuals in the group to which the study applies

sample

a subgroup of the population co-opted to participate in the study

representative sample

a smaller group that gives a "snapshot" of the total population

(simple) random sample

a sample that theoretically represents a population well because each member has an equal chance of inclusion (we want our findings to be generalizable)

stratified sampling

a method of sampling from a population which is partitioned into subgroups (not on AP Exam)

cluster sampling

find pre-existing subpopulations in the population (aka clusters); select a simple random sample of clusters is selected from the population (not on AP exam)

convenience sample

selecting whomever is most easily available

random assignment

assigning participants to experimental and control groups by chance, thus minimizing preexisting differences between the different groups

controlled experiment

the researcher systematically manipulates a variable under specified conditions and observes the response

temporality

"A" must be changed first before "B" can be affected

elimination of confounding variables

only one or several variables are being manipulated; all other conditions remain the same!

sampling bias

accidentally creating a subgroup that shares some common characteristic other than the one(s) that are the focus of the study

confounding variable

something that the researchers did not measure / failed to anticipate that could create different results for different groups in the study; any variable/factor that can (unexpectedly) have undue influence on the results of the study; differences between the experimental group and the control group other than those resulting from the independent variable

experimental group/condition

the group that receives the treatment (i.e., is the primary focus of the experiment)

control group/condition

the group that does not receive the treatment (i.e., provides a baseline level for understanding the effects of the treatment)

independent variable (iv)

the variable/factor manipulated by the experimenter whose effect is being studied (i.e., the theoretical cause of the relationship researchers are interested in)

dependent variable (dv)

the variable/factor that may change in response to the addition/removal (or changes in) the independent variable (i.e., the theoretical effect of the relationship researchers are interested in)

between-groups design

control group and experimental group(s) are different people

within-groups design (aka repeated-measures design)

control group and experimental group(s) are the same people (i.e., multiple conditions are administered to the same participants

demand characteristics

clues participants discover about the purpose of the study (e.g., rumors) and how they should respond

placebo

an imitation drug (i.e., a fake pill) that lacks the active ingredient of the medicine given to the control group

placebo effect

when participants of the control group (i.e., people given the fake drug) experience changes without being subject to experimental manipulation

single-blind study

a research design in which the participants do not know which treatment group - experimental or control - they are in (used to minimize the influence of demand characteristics)

double-blind study

a research design in which neither the experimenter nor the participants know who is in the experimental group and who is in the control group (used to minimize the influence of experimenter bias and demand characteristics)

quasi-experimental research design

similar to controlled experiments, but participants are not randomly assigned

operational definition

precise definition of a variable being observed

correlation coefficient

an standardized value of the strength and direction of the relationship between two variables

measures of central tendency

indices of the average or most typical scores for a set of research data or distribution

median

the middle score when the set of data is ordered by size

mean

the arithmetic average of the scores

mode

the most frequently occurring score in the data

frequency distribution

a histogram that shows the likelihood of endorsement for a particular value or category

normally distributed

the mean, median and modal are all equal to one another

negatively skewed

scores all squeezed into the right end of the distribution

positively skewed

scores all squeezed into the left end of the distribution

variability

the spread or dispersion of scores for a set of research data or distribution

range

the largest score minus the smallest score

sum of squares

the difference between each value and the mean, squaring the difference between each value and the mean (to eliminate negative signs), and then summing the squared differences

variance

the average of the sum of squares (N - 1 rather than N used to give a more accurate estimate of variance)

standard deviation

the square root of variance; tells us on average how much scores deviate from the average score (i.e., how much the scores group together / how dispersed they are)

covariance (cov)

the degree to which variables vary/change together (i.e., covary)

correlation (r; 𝜌 "roe")

covariance divided by the product of the standard deviations for variables x and y; a standardized measure of the strength and direction of the relationship between two variables

the normal distribution (aka the normal curve)

a symmetrical, bell-shaped curve that described the distribution of many types of data; most scores fall near the mean (~ 68% within 1 SD) and fewer and fewer near the extremes

meta-analysis

the process of conducting/collecting the results of multiple studies, combining the results (e.g., effect sizes) and creating a composite estimate based on those results

z-scores

standardized scores (measured in SD); z-score = +1.9 would mean that that particular student's score is +1.9 SD away from the mean of the population

inferential statistics

estimates (based on the information collected in our study) that help to generalize what we see in our study to understanding the whole population (i.e., estimations of population means, differences in means, correlations, etc. based on the results of our study)

statistical significance (α, "alpha")

the likelihood of an effect size (difference in means, correlation coefficient, regression coefficient) being as large as it is by random chance (p values are compared against the alpha value; if alpha =.05, and p < .05 for our effect size, then our findings are statistically significant)

parameter

the value (e.g., mean, difference in means, correlation coefficient, etc.) for the population of interest

statistic

the value (e.g., mean, difference in means, correlation coefficient, etc.) for your study sample (i.e., the group of people you observed or surveyed)

power (1 - β)

the likelihood that we detect a difference that is present (e.g., if we set power at .8, then there is an 80% chance that we will correctly reject the null hypothesis)

null hypothesis (h0; "h-naught")

no real effect exists (i.e., the difference in means, correlation coefficient, regression coefficient, etc., is as high as it is because of random chance) (e.g., pre- and post- means / means of two groups are the same)

alternative hypothesis (h1: "h-one")

a real effect exists (i.e., the difference in means, correlation coefficient, regression coefficient, etc., is as high as it is because there is some real relationship, probably one worth investigating further) (e.g., pre- and post- means are different)

type 1 error (alpha error)

detecting an effect when no effect exists (rejecting the null hypothesis when we should not reject it)

type 2 error (beta error)

failing to detect an effect when we should detect one (failing to reject the null hypothesis when we should reject it)

reliability

the consistency of our measurement

validity

whether a test measures what it is intended to measure (i.e., the accuracy of the test)