Summary: Management Research Methods 2

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  • 1 ANOVA

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  • When can one use ANOVA?

    - The OV is quantitative
    - The PV is categorical, so has two or more categories (0,2 or 4 beers predict if something will happen)
    - participants differ from each other (different test groups do not have the same participants)
    - population is normally distributed
    - populations must have the same variance
  • Variance testing can distinguish two tests, which two?

    Variance testing within groups
    Variance testing between groups (this is the one that says the most)
  • What does the F-test tell (ANOVA)?

    Variance between sample means / variance within the samples


    Variance between sample means = mean sum of squares of the model / Degrees of Freedom (number of groups - 1)

    Variance within the samples = Mean square residuals / Degrees of Freedom (number of participants - number of groups)
  • When is there effect from a PV on an OV?

    When the explained variance (between groups) is large relative to the unexplained variance (within groups) --> High F score
  • What is a Brown-Forsyth or Welch test?

    It is a criterion that tells if ANOVA can be done P > 0.05
  • What happens with R2 when there is only one PV?

    Than R2 becomes eta2
  • A T-test cannot be done to test for statistical evidence because there are used more than 2 groups to test (3x40N). Why can one not do multiple t-tests on these groups to find evidence?

    Because of alpha inflation (type 1 error)

    To test with 3 groups, three t-tests have to be done.

    1-0.95 = 0.05
    1-0.95^3 = 0.14
  • What are the two criteria for planned contrast tets?

    1. Sum of the weights must be 0
    2. If multiple contrasts are done (so multiple hypotheses are tested) they must be orthogonal. This means that the multiplied comparison of the tetst must be 0. 


    Example: H1 = group 2 > group 3 --> 0, 1, -1
                    H2 = group 1 > rest --> 1, -0.5, -0,5

    multiplied comparison: 
    0*1 = 0
    1*-0.5 = -0,5
    -1*-0.5 = 0.5

    These added up is 0, so they are orthogonal!
  • What does the Levene probability tell?

    If the significance is >0.05, than equal variances can be assumed.
  • What is a post hoc test?

    Statistical test afterwards to check the reliability of the earlier tetst done.
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