AP Statistics

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AP Statistics
2013-11-14 23:00:15

Vocabulary for Statistics. Chapter 11-13.
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  1. Random Numbers
    An outcome is random if we know the possible values it can have but not which particular value it takes.
  2. Simulate
    A simulation models a real world situation by using random-digit outcomes to mimic the uncertainty of a response variable of interest.
  3. Trial
    The sequence of several components representing events that we are pretending will take place.
  4. Response Variable
    Values of the response variable record the results of each trial with respect to what we were interested in.
  5. Population
    Entire group of individuals or instances about whom we hope to learn. (of interest)
  6. Sample
    A (representative) subset of a population, examined in hope of learning about the population.
  7. Bias
    Any systematic failure of a sampling method to represent its population is bias. Biased sampling method tends to be overestimated or underestimated parameters.
  8. Census
    A sample that consist of the entire population.
  9. Population Parameter
    A numerically valued attribute of a model for a population.
  10. Sample Statistic
    Statistic are values calculated for sample data. Those that correspond to, and thus estimate, a population parameter, are of a particular interest.
  11. Experiment
    An experiment manipulates factor levels to create treatments, randomly assigns subjects to these treatment levels, and then compares the response of the subject group across treatment levels.
  12. Factor
    A variable whose levels are manipulated by the experimenter.
  13. Treatment
    A process, intervention or other controlled circumstance applied to randomly assigned experimental units.
  14. Subjects
    Individuals on whom an experiment is performed (If they are humans)
  15. Experimental Units
    Individuals on whom an experiment is performed (if they are not human)
  16. Stratified Sampling
    A sampling design in which the population is divided into several sub-populations, or strata, and random samples are then drawn from each stratum.
  17. Cluster Sampling
    A sampling design in which entire groups, or clusters, are chosen at random. Cluster sampling is usually selected as a matter of convenience, practicality, or cost. Each cluster should be representative of the population, so all the clusters should be heterogeneous and similar to each other.
  18. Multistage Sampling
    Sampling schemes that combine several sampling methods are called multistage samples.
  19. Systematic Sampling
    A sample drawn by selecting individuals systematically from a sampling frame and the variable of interest, a systematic sample can be representative.
  20. Control
    Aspects of the experiment that we know may have an effect on the response but that are not the factors being studied.
  21. Randomize
    Subjects to treatments to even out effects that we cannot control.
  22. Replicate
    Over as many subjects as possible.
  23. Block
    Reduce the effects of identifiable attributes of the subjects that cannot be controlled.