BIOL2022 L06 ANOVA in practice. Why do it? Analyses with more than two means; interactions

Descripción

Module 1, Lecture 6 By the end of this lecture you should understand: - Why we need ANOVA - Entering data and running a 1-way ANOVA - Interpreting a 1-way ANOVA - Entering data and running a 2-way orthogonal ANOVA - Interpretation of one of those ^^
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Resumen del Recurso

Pregunta 1

Pregunta
ANOVA vs t-tests: Fundamentally, what can ANOVA do that t-tests can’t?
Respuesta
  • Work with more than 2 means
  • Cook steak fuckin’ perfectly
  • Compare means directionally

Pregunta 2

Pregunta
Homogeneity of variance: Levene’s and Cochran’s are different tests for this homogeneity/heterogeneity of variance. If they are found to be significant (P<0.05), this means:
Respuesta
  • Need to transform first
  • Data is good, go ahead

Pregunta 3

Pregunta
Homogeneity of variance: Levene’s and Cochran’s are different tests for this homogeneity/heterogeneity of variance. If they are found to be not significant (P>0.05), this means:
Respuesta
  • Need to transform data first
  • Data is good, go ahead

Pregunta 4

Pregunta
ANOVA is good an all that, but: Data [blank_start]___________[blank_end]; Normality [blank_start]____________[blank_end]; Variance [blank_start]____________[blank_end].
Respuesta
  • must be independent
  • isn’t important
  • must be homogeneous
  • need not be independent
  • need not be homogeneous
  • is important
  • must be independent
  • isn’t important
  • must be homogeneous
  • need not be independent
  • need not be homogeneous
  • is important
  • must be independent
  • isn’t important
  • must be homogeneous
  • need not be independent
  • need not be homogeneous
  • is important

Pregunta 5

Pregunta
What conclusion(s) can be drawn from this 2-way ANOVA?
Respuesta
  • Vegetation and Disturbance have a significant interaction
  • Vegetation has a significant effect
  • Disturbance has a significant effect
  • No significance can be drawn from this ANOVA
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