AP Statistics Chapter 4

Population

The entire group of people you want information about in a statistical study.

Census

Collects data from every individual in the population.

Sample

A subset of individuals in the population from which we actually collect data.

Convenience Sample

Choosing individuals from the population who are easy to reach results in.

Bias

Consistently overestimate or consistently underestimate the value you want to know.

Voluntary Response Sample

Consist of people who choose themselves by responding to a general invitation.

Random Sampling

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

Simple Random Sample (SRS)

Size n is chosen in such a way that every group of n individuals in the population has an equal chance to be selected as the sample.

Sampling Badly

Sampling using bias.

Stratified Random Sample

Start by classifying the population of similar individuals, called strata. Choose a separate SRS in each stratum and combine them to form the sample.

Strata

Classifying the population into groups of similar individuals.

Cluster Sample

Start by classifying the population into groups of individuals that are located near each other, called clusters. Choose an SRS of the clusters. All individuals in cluster are in sample.

Cluster

Classifying the population into groups of individuals that are located near each other.

Inference

The proves of drawing conclusions about a population on the bias of sample data.

Undercoverage

Occurs when some members of the population cannot be chosen in the sample.

Nonresponse

Occurs when an individual chosen for the sample can't be contacted or refuses to participate.

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

A specific condition applied to individuals in an experiment.

Experimental Units

The smallest collection of individuals to which treatments are applied.

Subjects

Human beings that are experimental units.

Factors

Explanatory variables in an experiment.

Level

A specific value of a factor within an experiment.

Random Assignment

Experimental units are assigned to treatments using a chance process.

Completely Randomized Design

The experimental units are assigned to the treatments completely by chance.

Control Groups

Provides a baseline for comparing the effects of other treatments.

Control

Keep other variables that might effect the response the same for all groups.

Replication

Using enough experimental units to distinguish a difference in the effects of treatments from chance variation due to random assignment.

Comparative Experiment

Experiment design that compares two or more treatments.

Blind

Experiment in which the subjects are unaware of which treatment they are receiving.

Double-Blind

Experiment in which neither the subjects nor those who interact with them and measure the response variable know which treatment a subject received.

Statistically Significant

An observed effect so large that it would rarely occur by chance.

Block

A group of experimental units that are known before the experiment to be similar in some way that is expected to affect the response to the treatments.

Blocking

The use of a stratified random sample rather tan a simple random sample when a population consist of groups of individuals that are "similar within but different between".

Randomized Block Design

The random assignment of experimental units to treatments is carried out separately within each block.

Matched Pairs

A type of randomized block design for comparing two treatments in which the idea is to create blocks by matching pairs of similar experimental units.

Scope of Inference

Random selection of individuals allows inference about the population and the random assignment of individuals to groups permits inference about cause and effect.

Causation

When changes in the explanatory variable cause changes in the response variable.

Data Ethics

Institutional review board, informed consent, and confidentiality.

Institutional Review Board

Reviews all planned studies in advance to assure the protection of the safety and well-being of the subjects.

Informed Consent

All individuals who are subjects in a study must give their permission before data is collected.

Confidential

Only statistical summaries for groups of subjects may be made public.

Sampling Well

Using random sampling. Letting chance choose the sample.

Experimenting Well

Comparing two or more treatments.

What can go wrong?

The use of bad sampling methods like convenience or voluntary response. Often leads to bias.