AP Stats Unit 3 Terminology

Bias

When a study systematically favors certain outcomes

Blinding

Refers to subjects not knowing which treatment they are receiving

Block design

Experimental design where subjects are divided into representative groups to bring up certain differences into the picture and reduce variation(for ex. blocking by gender, age, or race) and randomization then takes place within each block
P → reduce possible lurking variables

Census

An attempt to include the entire population

Cluster Sample

Involves dividing the population into heterogeneous groups called clusters and then picking everyone in a random sample of the clusters

Completely randomized design

An experimental design in which everyone has an equal chance of receiving any treatment

Confounding

When there is uncertainty as to which variable is causing an effect

Control group

A group given no treatment or a sham treatment

Double-blinding

Refers to subjects and those evaluating their responses not knowing who received which treatments
P → to reduce bias from both sides

Experimental study

Involves applying a treatment to one or more groups and observing the responses

Nonresponse bias

When a large fraction of those sampled do not respond

Observational study

Researchers merely observe (no treatments are applied)

Parameter

A numerical measurement describing some characteristic of the population

Placebo

A dummy or sham treatment such as a sugar pill (made to look like the actual pill)

Population

Entire set of items, events, people, objects, and so on that are of interest

population → parameter

Random assignment

In experiments, when subjects are randomly assigned to treatments

P→ to even out effects over which we have no control (confounding/lurking variables)

Random sampling

Use of chance in selecting a sample from a population
P→ to allow for generalization of conclusions

Response bias

When the question itself leads to misleading results
(for ex. ppl don’t want to be perceived as having unpopular, unsavory, or illegal views)

Sample

The part of the population actually examined
sample → statistics

Simple random sample (SRS)

A sample selected in such a way that every possible sample of the desired size has an equal chance of being selected (each element of the population will also have an equal chance of being selected)

Statistic

A numerical measurement describing some characteristic of the sample

Statistical significance

A resulting difference among treatment groups too large to be attributed to chance

Stratified random sample

Involves dividing the population into homogeneous groups called strata and then picking random samples from each of the strata

Systematic sample

Involves order the population, choosing a random point to start, and then picking every nth person for some n

Undercoverage bias

When part of the population is ignored (for ex. some telephone surveys miss all those who only have cell phones)

Voluntary response bias

When individuals choose whether or not to respond
(for ex. radio call-in shows and Internet surveys)