Statistics

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Author:
Mental86
ID:
2812
Filename:
Statistics
Updated:
2009-12-11 05:08:56
Tags:
statistics formulas
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statistics final
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  1. Each level of each independent variable has different subjects.
    Between-Subjects or Independent Group Design
  2. Each subject participates in all levels of all independent
    variables.
    • Within-Subjects or Repeated Measures
    • Group Design
  3. There must be at least two independent variables.

    Each subject participates in all levels of one
    independent variable but not the other.
    Mixed Group Design
  4. when the subjects try to figure out the experiment and then alter their
    behavior to either "help" the scientist or even hinder the scientist
    Demand Characteristics
  5. Standard Error of the Mean
  6. Standard Error of a Sample
  7. when you reject the null hypothesis when shouldn't have because the null
    hypothesis is actually true - there is not difference between your groups.
    Type I error
  8. when you fail to reject the null hypothesis when you should have because there really is a
    significant difference between your groups.
    Type II Error
  9. If the scientific hypothesis predicts a
    direction of the results, we say it is a
    One-Tailed Hypothesis
  10. If the scientific hypothesis does not
    predict a direction of the results, we say it is a
    Two-Tailed Hypothesis
  11. an analysis of an experimental design with one independent variable and a nominal
    dependent variable
    One-Way Chi-Square
  12. Chi-Square
  13. df = k -1
    Degrees of freedom for a Chi-Square
  14. fe of a Two-Way Chi-Square
  15. when you have two independent variables and a nominal dependent variable
    Two-Way Chi-Square
  16. df = (number of rows -1) x (number of columns -1)
    Degrees of Freedom for a Two-Way Chi-Square
  17. If your sample size
    is above 1000 (Comparing Sample to a Population
    Single Sample z-test
  18. Single Sample z-test formula
  19. If your sample size
    is below 1000 (Comparing Sample to Population)
    Single Sample t-test
  20. Single Sample t-test formula
  21. If your two sample groups are independent of each other
    t-test for Independent Groups
  22. t-test for Independent Groups formula
  23. Standard Error of the Difference for Independent Groups
  24. (n1 - 1) + (n2 - 1)
    df independent groups
  25. If the two samples are not independent of each other but
    instead are positively correlated to each other
    t-test for Correlated Groups
    • the standard
    • error of the difference
    • (correllated groups)
  26. number of pairs - 1
    df correlated groups
  27. t-test for correlated samples: using raw data
  28. D bar
    • The mean of all the
    • difference scores. Difference scores are calculated by subtracting each Y value
    • from its X pair value
  29. Standard Difference for Correlated Groups using the raw data
  30. F = MSbg / MSwg
    F ratio formula One-Way ANOVA
  31. MSbg = SSbg / dfbg
    MSbg formula One-Way ANOVA
  32. MSwg = SSwg / dfwg
    MSwg formula One-Way ANOVA
  33. dfbg = k - 1
    dfbg formula One-Way ANOVA
  34. dfwg =
    (n1 - 1) + (n2 - 1) + . . . + (nk - 1)
    dfwg formula One-Way ANOVA
  35. SSbg = [ (ΣX1)2 / n1 ) + (ΣX2)2 / n2 ) + . . . + (ΣXk)2 / nk ) ] - [ (ΣX1 + ΣX2 + . . . + ΣXk )2 / Ntotal ]
    SSbg formula One-Way ANOVA
  36. SSwg = [ (ΣX21 + ΣX22 + . . . + ΣX2k ) ] - [ (ΣX1)2 / n1 ) + (ΣX2)2 / n2 ) + . . . + (ΣXk)2 / nk ) ]
    SSwg formula One-Way ANOVA
  37. dfN
    dfbg
  38. dfD
    dfwg
  39. Nominal Dependent Variable Data
    Chi-Square (X2)
  40. Ordinal Dependent Variable Data
    An ordinal statistic
  41. Interval/Ratio Dependent Variable
    2+ Factors (Independent Variables)
    Two-Way ANOVA
  42. Interval/Ratio Dependent Variable
    1 Factor (Independent Variables)
    2 Levels (i.e. control and experiment)
    T-Test
  43. Interval/Ratio Dependent Variable
    1 Factor (Independent Variables)
    3+ Levels (i.e. control, experiment1, experiment2)
    One-Way ANOVA

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