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The whole entire unit 4 vocabulary.
Convenience Sampling
Selects individuals from the population who are easy to reach.
Bias
When the results of data collection always under- or overestimates the parameter.
Voluntary Response Sampling
Allows people to choose to be in the sample by responding to a general invitation.
Simple Random Sample (SRS)
A mode of data collection in which every person in the population has an equal chance of being chosen (without first being split into subgroups).
Parameter (p)
A # that describes the population.Ā Most parameters are unknowable in the real world because the population is too big to measure accurately.
Statistic (p-hat)
A number that describes a sample.Ā If the sample is representative of the population, then the known statistics will be very close to the unknowable parameter.
Variability
How the statistic varies from sample to sample. The ideal sample has low variability and low bias.
Proportion
A decimal value (sometimes a fraction).
Margin of error
MOE attempts to put a numerical value on how inexact we think we might be.
Kinds of nonsampling errors
Stratified sample
Break the sampling frame into small groups. Within each group the subjects should be similar.
Strata
Subjects in a stratified sample that get broken into smaller group (and they have something in common).
Stratified Random Sampling
Selects sample by choosing an SRS from each stratum and combining the SRSs into one overall sample.
Sampling frame
The list from which the sample is actually chosen.
Clusters
Group of individuals in the population that are located near each other.
Cluster sampling
Selects sample by randomly choosing clusters and including each member of the selected clusters in the sample.
Undercoverage
When some members of the population are less likely to be chosen or cannot be chosen in a sample.
Nonresponse
Occurs when an individual chosen for the sample cant be contacted or refuses to participate.
Response bias
Occurs when there is a systematic pattern of inaccurate answers to a survey question.
Observational study
Observes individuals and measures variables of interest but does not attempt to influence the responses.
Confounding
When it is impossible to tell if the results of an experiment are from the treatment or some other variable.
Explanatory Variable
A treatment applied to the individuals in an experiment.
Response variable
What is measured after a study is conducted.
Control group
Baseline for comparing the effects of other treatment.
Double Blind
Neither subjects nor those interact with them and measure the response variable will know which treatment a subject received.
Single Blind
When the treatment group donāt know which which treatment they are receiving.
Block Design
A group of two or more subjects that are the same get randomly assigned to one group, a different group of two or more subjects with something in common get randomly assigned to a different group. An example of this is separating subjects by gender and randomly assigning them groups, though still adhering to their own gender.
Matched Pairs Design
A group of two subjects that are the same and get different treatments.
Statistically significant
When observed results of a study are too unusual to be explained by chance alone.
Institutional Review Board
Reviews all planned studies to protect rights and welfare of human subjects.
Valid measurement
A measurement is valid if it accurately represents what is being measured.
Reliable
A measurement is reliable if it gives similar results when repeated on the same subject.
Note 
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