AP Statistics Designing Studies

population

group of individuals that we want information about

census

collects data from every individual in the population

sample

subset of individuals in the population from which we collect data

sample survey

study that uses an organized plan to choose a sample that represents some specific population

convenience sample

choosing individuals from the population who are easy to reach, produces unrepresentative data

voluntary response samples

people decide whether to join in a sample to an open invitation, people with strong opinions are most likely to respond

random sampling

using a chance process to determine which members of a population are included in the sample

simple random sample

size n, is chosen so that every group of n individuals in the population has an equal chance to be selected in the sample

stratified random sample

population is classified into groups called strata, a separate SRS is chosen in each strata and combined to form a sample

cluster sample

population is classified into groups that are located near each other, called clusters, an SRS is chosen of the clusters. All individuals in the chosen clusters are included in the sample

undercoverage

occurs when some members of the population cannot be chosen in a sample

nonresponse

occurs when an individual chosen for a sample can't be contacted or refuses to participate

response bias

systematic pattern of incorrect responses in a sample survey

wording of questions bias

difference in the questions that leads to different responses

observational study

observes individuals and measures variables of interest but does not attempt to influence the responses

experiment

deliberately imposes some treatment on individuals to measure their responses

confounding

occurs when two variables are associated in such a way that their effects on a response variable cannot be distinguished from each other

treatment

specific condition applied to individuals in an experiment

experimental units

smallest collection of individuals to which treatments are applied

random assignment

experimental units are assigned to treatments using a chance process

Principles of experimental design

comparison

random assignment

control

replication

completely randomized design

treatments are assigned to all the experimental units completely by chance

control group

receives an inactive treatment or existing baseline treatment

placebo effect

response to dummy treatment

double blind experiment

neither the subjects nor those who interact with them know which treatment a subject received

statistically significant

whether treatments are larger than we would expect to see if only by chance, an observed effect so large that it would rarely effect by chance, implies causation in a well designed experiment

block

a group of experimental units that are known to be similar in some way before the treatment and it expected to affect response to the treatments

randomized block design

random assignment of experimental units to treatments is carried out separately by block

matched pairs design

randomized block experiment in which each block consists of a matched pair or similar experimental units, chance is used to determine which unit in each pair gets each treatment, could be a single unit that receives both treatments

random assignment to groups

inference about cause and effect

random selection

inference about population

establishing causation

association is strong and consistent, larger values of the explanatory variables are associated with stronger responses, alleged cause is plausible and precedes the effect