ap stats -- unit 3

the entire group of individuals that information is about

subset of the population from which data is collected

something that models some attribute of population

value calculated from sample data

a systematic failure of a sampling method to represent the population

each individual is equally likely to be chosen for the sample, as well as each subset (unbiased)

self-selected sampling frame; the only people that participate have strong opinions; underrepresents the population that doesn’t have strong opinions

only surveying individuals that are easily accessible; e.g. only surveying seniors in ap stats instead of all seniors

refers to whether an estimator tends to over/underestimate the perameter

how much estimates vary from sample to sample

population is divided into several heterogenous groups; subgroups are randomly selected and all individuals from subgroups are included in the sample

starting point is randomly selected, then a rule is used to select (ex. starting at #5, every 11th)

population is divided into homogenous groups and a random sample is taken from each group

homogenous groups within a population

e.g. randomly select 3 states, then randomly select 2 cities in each state

not a sample; surveys every member of a population

part of the population has a reduced chance of being included in the sample; therefore, the sample is unrepresentative of the population (convenience)

individuals chosen as part of a sample group do not respond (e.g. ignoring a phone call)

comprised entirely of volunteers (with strong opinions) and tends to not be representative of the population

issues with data collection; influential question wording/tone or influential interviewers

list from which the sample is drawn

observe individuals without intervention (no treatments imposed)

collection of data that has already taken place

collection of data in real time

treatments are imposed; must be randomly assigned to determine causation

subjects/units that receive treatment

explanatory variables - what is manipulated

different values of a factor

a combination of factors and levels

when other variables associated with a factor have an effect on the response; prevents us from knowing if response is due to the factor or the other variable

used to provide baseline data for comparison; may receive placebo or no treatment

when the subject does not know which treatment they are receiving

when the subject or the administer do not know which treatment the subject is receiving

showing a response to a fake treatment

randomly and evenly design units to treatments

must have 2+ treatments

keep all variables (besides treatments) the same to reduce confounding

using enough experimental units to distinguish differences and show variability

group of experimental units that are similar in some way that effects the response

choose blocks to reduce variability in responses and randomly assign treatments in each block

special type of block design in which two similar units are paired up and split into different treatment groups

when results are way too unusual to be a coincidence

models a random process in order to estimate a probability

can generalize to the population we sampled

balances groups to determine causation