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Statistics 210

  1. Independent Variable
    The variable manipulated by the experimenter. It is a feature of a task given to subjects or of the external or internal environment
  2. Dependent Variable
    The response measure of an experiment. It is the selected behavior which is measured to gauge the effect of the independent variable. The term also refers to the criterion variable, or Y variable, in a correlational study.
  3. Random Sampling
    A procedure in which each member of the population has an equally likely change of being included in the sample.
  4. Confounding (Nuisance) Variables
    One or more independent variables that vary systematically with the variable of interest, decreasing the ability to make causal inferences.

    A potential independent variable that is not to be manipulted in an experiment that must be neutralized to prevent confounding with the treatment variables.
  5. Control (Placebo) Group
    Group assigned to a reference, or baseline, condition consisting of the absence of a specific experimental treatment. Sometimes referred to as a placebo group when included in an experiment involving the administration of drugs.
  6. Between-Groups Variability
    Differences among the treatment means; reflects the effects of the treatments plus chance factors (experimental error)
  7. Within-Group Variability
    A measure of variability based on the variaition of subjects treated alike; provides an estimate of experimental error
  8. Treatment Effect
    The differences among the treatment means in the population. A theoretical quantity that cannot be observed directly in an experiment.
  9. Experimental Error
    Uncontrolled sources of variability (primarily individual differences) assumed to occur randomly during the course of an experiment.
  10. Null Hypothesis
    The statistical hypothesis evaluated by hypothesis testing. Usually expressed as the absence of a relationship in the population and represented by the symbol H0.
  11. Alternative Hypothesis
    The hypothesis that is accepted when the null hypothesis is rejected; represented by the symbol H1.
  12. Analysis Variance
    A statistical analysis involving the comparison of variances that reflect different sources of variability; abbreviated ANOVA.
  13. Grand Mean
    The mean calculated from all the abservations in a study (ȲT)
  14. Significance Level (α)
    The probability (α) with which an experimenter is willing to reject the null hypothesis when in fact it is correct. Also known as the probability of a type I error.
  15. Planned Comparisons
    Analytical comparisons specified before the start of an experiment
  16. Unplanned Comparisons
    Comparisons not specified at the start of an experiment and conducted after the data have been examined. Also known as post hoc or multiple comparisons.
  17. Type I Error
    An error of statistical inference that occurs when the null hypothesis is true but is rejected. An error of "seeing too much in the data."
  18. Type II Error
    An error of statistical inference that occurs when the null hypothesis is false but is retained. An error of "not seeing enough in the data." Also notated by Beta (β).
  19. Familywise Type I Error
    The probability of committing a type I error over a set of statistical tests; approximately equal to the sum of the separate per comparison probabilities. Represented by the symbol FW.
  20. Calculating the Grand Mean
    ȲT=T/(a)(n)

    • T: total sum of scores
    • a: # of treatment levels
    • n: # of subjects assigned to each treatment
Author
Ashlie
ID
42198
Card Set
Statistics 210
Description
Stats Vocab
Updated

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