BIOL2022 L13 Dealing with CLASS INDEPENDENT VARIABLES

Beschreibung

Module 2, Lecture 2 Learning outcomes: • Dealing with class independent variables • Type of analysis driven by types of variables • ANOVA – one useful parametric test • Reliable analyses depend on assumptions met • Transforming can “improve” data • Today, there are alternatives to transforming
Michael Jardine
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Michael Jardine
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Zusammenfassung der Ressource

Frage 1

Frage
What conditions must be present in order to use an independent t-test? A [blank_start]____________[blank_end] dependent variable; A [blank_start]____________[blank_end] independent variable (with [blank_start]____________[blank_end] levels).
Antworten
  • Continuous
  • Class
  • 2
  • >2
  • ≥2 (>=2)

Frage 2

Frage
What conditions must be present in order to use a 1-way ANOVA? A [blank_start]____________[blank_end] dependent variable; A [blank_start]____________[blank_end] independent variable (with [blank_start]____________[blank_end] levels).
Antworten
  • Continuous
  • Class
  • ≥2 (>=2)
  • 2
  • >2

Frage 3

Frage
In an ANOVA, the F value is obtained by the formula: ---- Groups MS / Error MS ---- ...where Groups MS = Groups SS / Groups DF ...and Error MS = Error SS / Error DF In these, what are the following defined as? DF = [blank_start]____________[blank_end]; MS = [blank_start]____________[blank_end]; SS = [blank_start]____________[blank_end]; …therefore: Groups MS represents [blank_start]____________[blank_end], whereas Error MS represents = [blank_start]____________[blank_end].
Antworten
  • degrees of freedom
  • mean squared deviation from the mean
  • mean squares
  • sum of squared deviation from the mean
  • sum of squares
  • BETWEEN groups’ mean-squares
  • WITHIN groups’ mean-squares
  • BSOD

Frage 4

Frage
When reporting an ANOVA, what do each of the following numbers represent? Options are: #1 - df BETWEEN groups (# of treatment groups) #2 - df BETWEEN groups (# of treatment groups - 1) #3 - df BETWEEN groups ( (# of treatment groups) x (# of samples in each group) ) #4 - df BETWEEN groups ( (# of treatment groups - 1) x (# of samples in each group - 1) ) #5 - df WITHIN groups (# of treatment groups) #6 - df WITHIN groups (# of treatment groups - 1) #7 - df WITHIN groups ( (# of treatment groups) x (# of samples in each group) ) #8 - df WITHIN groups ( (# of treatment groups - 1) x (# of samples in each group - 1) )
Antworten
  • #2 BETWEEN
  • #1 BETWEEN
  • #3 BETWEEN
  • #4 BETWEEN
  • #5 WITHIN
  • #6 WITHIN
  • #7 WITHIN
  • #8 WITHIN

Frage 5

Frage
Homoscedasticity vs heteroscedasticity: Heteroscedasticity means:
Antworten
  • Variance is unequal, e.g. error gets larger on one side
  • Variance is unequal, e.g. more samples on one side
  • Distribution is unequal, e.g. error gets larger on one side
  • Distribution is unequal, e.g. more samples on one side

Frage 6

Frage
In order to perform an ANOVA, you should transform if your data is:
Antworten
  • Heteroscedastic
  • Homoscedastic
  • Really shitty

Frage 7

Frage
Question: “Is aerobic enzyme activity greater in males than females? Dependent variable: [blank_start]____________[blank_end], which is a [blank_start]____________[blank_end] variable; Independent variable: [blank_start]____________[blank_end], which is a [blank_start]____________[blank_end] variable.
Antworten
  • Aerobic enzyme activity
  • Continuous
  • Sex
  • Class
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