AP Stats Ch. 4 Vocab Flashcards
Sample
a (representative) subset of a population
Population
the entire group of individuals or instances about whom we hope to learn from
Sample Survey
a study that asks questions of a sample drawn from some population in hopes of learning something about the whole
Voluntary Response
sampling design where individuals can choose to participate (biased because some groups aren’t represented)
Confounded
when levels of one factor are associated with the levels of another factor so their effects can’t be separated
Design
type of sampling
Convenience Sampling
individuals are chosen based of who is easily available
Biased
any systematic failure of a sampling method
Simple Random Sampling
sampling design in which each set of “x” elements in the population has an equal chance of being selected
Table of Random Digits
used for SRS
Stratified Random Sampling
sampling design in which the population is divided into several strata and random samples are drawn from each strata
Cluster Sampling
sampling design in which entire groups are chosen at random
Undercoverage
type of bias that is problematic because some groups aren’t represented in the sample
Nonresponse
type of bias that is problematic because the intended sample is incomplete
Response Bias
type of bias that is problematic because false info may be given
Sampling Frame
a list of individuals from whom the sample is drawn
Systematic Random Sample
sample drawn by selecting an individual from a list every nth time
Inference
inferring something about a population by examining a sample
Strata
name of groups that have been divided from the whole when stratified random sampling is used
Parameter
number (quantity) or quality that describes a population
Observational Study
Observes individuals and measures but doesn’t influence response
Statistic
number (quantity) or quality that describes a sample
Experiment
Deliberately imposes some treatment on individuals to measure their response
Lurking Variable
Variable that isn’t explanatory or response but influences in some way
Experimental Units
Smallest collection of individuals to which treatments are applied
Subjects
Human units
Treatment
A specific condition applied to the individuals
Factors
Combination of values of the explanatory variable
Levels
Combing specific values to create a treatment
Random Assignment
Experimental units are assigned to the treatments at random
Comparative Design
Compares 2 treatments
Completely Randomized Design
The treatments are assigned to all the experimental units by chance
Control Group
The baseline for comparing g the effects of other treatments
Principles of Statistical Design
- Control: for lurking variables that affect response; use comparative design and assure the difference is only the way treatments are administered
- Random Assignment: use impersonal chance to assign experimental units to treatments. Crests roughly equivalent groups
- Replication: use enough units so any differences can be distinguished
Placebo Effect
A dummy treatment. Assure the distribution of treatments is the same and subjects don’t know which treatment they are receiving.
Double-blind
Neither subjects or those who interact and measure the response variable know which treatment a subject receives.
Single-blind
Subjects know which treatment they are receiving but individuals who interact with them don’t
Statistically Significant
An observed effect so large 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
Randomized Block Design
The random assignment of experimental units to the treatments is carried out separately within each block.
Matched Pair Design
Create blocks by matching pairs if similar experimental units. 1 member gets 1 treatment first and the other member the other treatment
