Population
Entire group of individuals.
Sample
Part of the population from which information/data is actually collected. Information drawn is used to draw conclusions from the population.
Convenience samples
Individuals are chosen so that results can be reached easier. This produces unrepresentative data.
Bias
Systematically favors certain outcomes.
Voluntary response sample
Consists of people who choose themselves by responding to a general appeal. They have their own base opinion that is unwilling to change.
Simple Random Sample (SRS)
Size n consists of n individuals from the population chosen in such a way that every set of n individuals has an equal chance of being chosen.
Stratified random sample
The sampling of important groups (called STRATA) within the population separately. SRS are chosen within the strata.
Cluster sample
A selectikon of a group of individuals that are "near" one another.
Undercoverage
When some groups in the population are left out of the sample choosing process.
Nonresponse
When people choose whether to respond or not. Only occurs after a sample has been selected.
Response bias
Systematic pattern of incorrect responses in a sample survey; can give faulty and inaccurate results.
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 response.
Explanatory variable
May help explain or influence changes in a response variable (manipulated).
Level
Different levels of factor.
Treatment
A specific condition applied to the individual(s) in an experiment.
Response variable
Measures an outcome of a study. Variable is measured.
Lurking variable
A variable that is not among the explanatory or response variables in a study but may influence the response variable.
Confounding
The effects of two variables on a response variable cannot be separated (distinguished) from each other - influences the response.
Experimental units
Smallest collection of individuals to which treatments are applied too.
Subjects
Human experimental units.
Completely Randomized Design
Treatments are assigned to all the experiemental units completely by chance; subjects are assigned to treatments by chance, split into equal groups then the treamtnet is exectured. All must receive an equal chance to receive treatments.
Control
Comparison of treatments. Used to compare affected data with a variable to on that didn't see to differences amonf that data and draw conclusions.
Random assignment
Helps balance out the effects of lurking variables that can't be controlled. Formed groups that should be similar in all respects before the treamtnent(s) is(are) applied.
Replication
Use enough experiemental units in each group so that any differences in the effects of the treaments can be distinguished from chance differences between thr groups.
Placebo effect
Response to a dummy effect (anticipation of an effect).
Single-blind
Subjects are unaware of the treament, but people interacting with them and measuring response variables know.
Double-blind
Neither subjects nor those who interact with them and measure response variables know which treatment a subject received.
Statistically significant
An observed effect so large that it would rarely occur by chance.
Block
Group of experiemental units that are known before the experiment to be similar in some way tjat is expected to affect the response to the treatments. Base blocks on the most important unavoidable sources of lurking variables among the experimental units.
Matched pairs design
Common type of randomized block design for comparing two treatments. 1. Subjects that are similar. 2. Or giving each subject BOTH treatments.