Test
BIOL2022 L16 INFORMATION-THEORETIC METHODS vs NULL HYPOTHESIS TESTING
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Preguntas del test (7)
1Which of the following are alternatives to null-hypothesis testing?
- AInformation Theory
- BBayesian approaches
- CTwo-factor ANOVA
2AIC stands for [blank_start]________[blank_end] [blank_start]________[blank_end] [blank_start]________[blank_end].
- AAkaike
- BAkake
- CAlternative
- DArbitrary
- EInformation
- FInformatic
- GInformatics
- HI can't think of a 4th option here
- ICriterion
- JCriteria
- KCritique
- LComputation
- MCritiques
- NComputations
3Which of the following are considered part of Information Theory?
- ASimplicity
- BParsimony
- CMultiple working hypotheses
- D‘Strength of Evidence’
- ENull hypothesis testing
- FP-hacking
4AIC determines that which model is “best”?
- AModel 1
- BModel 2
- CModel 3
- DInsufficient information
5True or false: AIC tells you which model is best.
- AVerdadero
- BFalso
6True or false: AIC tells you how good each model is.
- AVerdadero
- BFalso
7Which of the following is the Akaike Weight?
- ARelative likelihood of the model
- BDifference between the model AIC and the minimum AIC
- CAIC adjusted for finite sample size
- DAIC adjusted for infinite sample size
- ENone of the above
Información
- Descripción
- 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
- Autor
- Michael Jardine
- Idioma
- English
- Visitas
- 391
- Etiquetas
- Valoración
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