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0 Exakte Antworten 33 Text Antworten 10 Multiple Choice Antworten
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Measures of Central Tendency

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4 measures of variation?

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when data distribution is symmetrical then

mean ≠ median

mean = median

mode = midrange = midhinge

mode ≠ midrange ≠ midhinge

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What is the empirical rule?

68% within \(1\sigma\)

95% within \(2\sigma\)


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What is a Type I error?

error of falsely rejecting a null hypothesis

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What is a Type II error?

incorrectly retaining a false null hypothesis

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What is R2?

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Multiplied by 100 it represents the percentage of variation in the outcome that can be explained by the model

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What are the 4 basic assumptions when performing multiple regression?

  • No (perfect) multicollinearity: There should be no perfect linear relationship between two or more of the predictors

    • Variance inflation factor (VIF): can be used to assess and eliminate multicollinearity. VIF is a statistical value that identifies what independent variable(s) contribute to multicollinearity and should be removed. Any variable with VIF of greater than 10 should be removed.

  • Normally distributed errors: it is assumed that the residuals in the model are normally distributed values with a mean of 0, i.e. they are most frequently zero, close to zero and rarely much greater than zero

  • Homoscedasticity: at each level of the predictor variable(s), the variance of the residual terms should be constant

  • Linearity: The inclusion of each independent variable preserves the straight-line assumptions of multiple regression analysis