data analysis in biology at University of Zürich

Flashcards and summaries for data analysis in biology at the University of Zürich

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Exemplary flashcards for data analysis in biology at the University of Zürich on StudySmarter:

binary data

Exemplary flashcards for data analysis in biology at the University of Zürich on StudySmarter:

binomial data 

Exemplary flashcards for data analysis in biology at the University of Zürich on StudySmarter:

what is the question in binary/binomial regression?

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Exemplary flashcards for data analysis in biology at the University of Zürich on StudySmarter:

what are the problems when using a linear regression for binomial data?

Exemplary flashcards for data analysis in biology at the University of Zürich on StudySmarter:

what is the problem when using a poisson regression for binomial data?

Exemplary flashcards for data analysis in biology at the University of Zürich on StudySmarter:

count data definition

Exemplary flashcards for data analysis in biology at the University of Zürich on StudySmarter:

binomial data definition

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Exemplary flashcards for data analysis in biology at the University of Zürich on StudySmarter:

when can we use the diagnostic plots with a binomial model?

Exemplary flashcards for data analysis in biology at the University of Zürich on StudySmarter:

what does overdispersion mean?

Exemplary flashcards for data analysis in biology at the University of Zürich on StudySmarter:

how is the variance determined in the binomial regression?

Exemplary flashcards for data analysis in biology at the University of Zürich on StudySmarter:

what is the problem with overdispersion?

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Exemplary flashcards for data analysis in biology at the University of Zürich on StudySmarter:

how to account in R for a overdipersed binomial model?

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Exemplary flashcards for data analysis in biology at the University of Zürich on StudySmarter:

data analysis in biology

binary data

 0 or 1 

data analysis in biology

binomial data 

something between 0 and 1

data analysis in biology

what is the question in binary/binomial regression?

which variables influence the probability p of the outcome

data analysis in biology

what are the problems when using a linear regression for binomial data?

  • linear regression leads to  impossible predicted probability values -> impossible predictions
  • residuals are nt normally distributed

data analysis in biology

what is the problem when using a poisson regression for binomial data?

impossibe predictions

data analysis in biology

count data definition

  • theoretically no upper limit
  • Counts cannot be expressed as a proportion

data analysis in biology

binomial data definition

  • aggregated version of many binary experiments
  • There is an upper limit
  • success can be expressed as a proportion

data analysis in biology

when can we use the diagnostic plots with a binomial model?

when we have aggregated data

data analysis in biology

what does overdispersion mean?

extra variability 

data analysis in biology

how is the variance determined in the binomial regression?

the variance is determined by the mean

Var(Y) =π (1-π ) 


data analysis in biology

what is the problem with overdispersion?

too small p-values

data analysis in biology

how to account in R for a overdipersed binomial model?

switch to a quasibinomial model

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