A statistical study of the entire group of individuals we want information about
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Census
Collects data from every individual in the population
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Sample
A set of individuals in the population from which we collect data
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Sample Survey
A study that collects data from a sample to learn about the population from which sample was selected
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Convenience sampling
Selects individuals from the population that are easy to reach
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Bias
The design of a statistical study
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Volunteer response sampling
Allows people to choose to be in the sample by responding to a general invitation
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Random
Involves using a chance to process to determine are included in the sample
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Sampling without replacement
An individual from a population can be selected only once
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Sampling with replacement
An individual from a population can be selected more than once
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Simple Random Sample (SRS)
Of size N is chosen in such a way that every group of N individuals in the population has an equal chance to be selected
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Strata
Groups of individuals in a population who share characteristics thought to be associated with the variables being measured
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Sampling
Selects a sample by choosing an SRS from each stratum and combining the SRS’s into one overall sample
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Cluster
A group of individuals in the population that are located near eachother
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Cluster Sampling
Selects a sample by randomly choosing clusters and including each member of the selected cluster
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Systematic Random Sampling
Selects a sample from an ordered arrangement of the population by randomly selecting one of the first individuals and choosing every individual thereafter.
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Undercoverage
Occurs when some members of the population are less likely to be chosen or cannot be chosen in a simple
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Nonresponse
Occurs when an individual chosen for the sample can’t be connected or refuses to participate
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Response Bias
Occurs when a systemic pattern of inaccurate answers to a survey question
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Observational Study
Observes individuals and measures variables of interest but does not attempt to influence the responses
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Response variable
Measures an outcome of a study
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Explanatory variable
May help explain or predict changes in response variable
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Experiment
An experiment deliberately imposes treatments (conditions) on individuals to measure their responses
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Placebo
A treatment that has no active ingredient, but is otherwise like other treatment
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Treatment
A specific condition applied to the individuals in any experiment
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Experimental Units
The object to which a treatment is randomly assigned
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Subjects
When the experiment units are human beings
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Factor levels
In an experiment, a factor is an explanatory variable that is manipulated and may cause a change in the response variable. The different are called levels.
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Control Group
Used to provide a baseline for comparing the effects of other treatments.
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Placebo Effect
Describes the fact that some subject in an experiment will respond favorably to any treatment even an inactive
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Double-blind
Neither the subjects nor those who interact with them and measure the response variable know which treatment a subject is receiving
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Single-blind
Either subjects or the people who interact with them and measure the response variable don’t know which treatment a subject is receiving
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Random Assignment
A random assignment means that the experimental units are assigned to treatments using a chance process
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Control
Means keeping other variables constant for all experimental wins
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Replication
Giving enough treatment to enough experiment units
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Confounding
Occurs when two variables are associated in such way that their effects on a response variable cannot be distinguished from each other
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Completely Randomized Design
The experimental units are assigned to the treatments completely at random
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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.
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Randomized block design
Random assignment of experimental units to treatments is carried out separately within each week
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Matched pair design
A common experimental design for comparing two treatments that use block for size 2
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Retroprespective
Examine existing data for a sample of individuals
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Prospective
Observational studies that track individuals into the future
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Sampling variability
The fact that different random samples of the same size from the same population produce different estimates
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Statistically significant
Observed results of a study are too unusual to be explained by chance
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Random selection
Individuals allow inference about the population from which the individuals were chosen
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Random assignment
Individuals to groups allows inference about cause and effect
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