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BIOL2022 L16 INFORMATION-THEORETIC METHODS vs NULL HYPOTHESIS TESTING

Michael Jardine 7 Fragen

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  1. 1Which of the following are alternatives to null-hypothesis testing?
    1. AInformation Theory
    2. BBayesian approaches
    3. CTwo-factor ANOVA
  2. 2AIC stands for [blank_start]________[blank_end] [blank_start]________[blank_end] [blank_start]________[blank_end].
    1. AAkaike
    2. BAkake
    3. CAlternative
    4. DArbitrary
    5. EInformation
    6. FInformatic
    7. GInformatics
    8. HI can't think of a 4th option here
    9. ICriterion
    10. JCriteria
    11. KCritique
    12. LComputation
    13. MCritiques
    14. NComputations
  3. 3Which of the following are considered part of Information Theory?
    1. ASimplicity
    2. BParsimony
    3. CMultiple working hypotheses
    4. D‘Strength of Evidence’
    5. ENull hypothesis testing
    6. FP-hacking
  4. 4AIC determines that which model is “best”?Bild zu Frage 4
    1. AModel 1
    2. BModel 2
    3. CModel 3
    4. DInsufficient information
  5. 5True or false: AIC tells you which model is best.
    1. ARichtig
    2. BFalsch
  6. 6True or false: AIC tells you how good each model is.
    1. ARichtig
    2. BFalsch
  7. 7Which of the following is the Akaike Weight?Bild zu Frage 7
    1. ARelative likelihood of the model
    2. BDifference between the model AIC and the minimum AIC
    3. CAIC adjusted for finite sample size
    4. DAIC adjusted for infinite sample size
    5. ENone of the above

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Beschreibung
Module 2, Lecture 5 No Learning Outcomes, but Summary: • Bayesian and Information Theory approaches: alternatives to null-hypothesis testing • AIC determines the model of best fit with the number of parameters • AIC is NOT a measurement of support for a model • Model averaging recognises uncertainty in models by calculating average parameters weighted by Akaike weights • Note: CANNOT undo bad sampling or poor experimental design
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