Shimada- Exam 2 Flashcards
phylogeny
evolutionary history of organisms
systematics phylogenetics
scientific study of the origin, evolution, and interrelationships of organisms
Willi Hennig
Cladistics
- methodologists
- one phylogenetic approach -> cladogram
- based on shared derived characters
- the more derived characters the more the two groups of organisms are closely related
- goal: look for monophyletic groups
- relatively objective (strength = repeatable)
taxon
named organism (at any taxonomic rank)
ex. sharks
rooted vs unrooted
notes
clade
means branch, taxon, species, or an entire lineage
- each line represents a taxon
node
speciation or divergent evolution took place
- pattern based should be talked about in cladograms
sister species/taxa
two species/taxa showing an immediate common ancestor
Ingroup vs Outgroup
set of organisms to find interrelationship
- outgroup is the reference organisms
character vs character state
attribute (physical/behavioral) have two alternate forms
polarity
- based on outgroup
- polarity of outgroup is ancestral state
- ex. blue + brown eyes tow attributes but don’t know which one is ancestral or derived
character matrix
finds polarity
shared derived characters
character by itself doesn’t show interrelationship between species
uniquely derived character
traits = homologous which makes a better tree (parsimonious)
Monophyletic
a complete lineage (natural taxon); all organisms in a lineage and their common ancestor
- ex. mammalia
- based on shared derived characters
Paraphyletic
an incomplete lineage (artificial taxon)
- ex. “traditional” reptilia
Polyphyletic
a misinterpreted lineage (artifical taxon)
- ex. Haematothermia (warm blooded)
Taxonomy
hierarchy of organismal classification: scientific study of naming, describing, and classifying organisms
Domain: Eucarya:
kingdom animalia
phylum chordata
class mammalia
order primates
family homonidae
genus homo
species “homo”-sapiens
Carlos Linnaeus
- taxonomy
-god created I organized
-made binomial nomenclature
Statistical types
Descriptive: basic description of data
- measure of central tendency (mean , median, mode)
- measure of dispersion/spread of #s (range & standard deviation)
Inferential: analysis to allow interpretation of the data
- involves hypothesis testing (w/ assumptions) (t-test, x2 test, correlation/regression analysis)
- generate a p-value to asses statistical significance
- p = the probability that the outcome of the
last test may occur by chance
- smaller p-value is better
statistical hypothesis
- null hypothesis (H0): no difference/association between groups
- alternative hypothesis (H1): there is a difference/association between groups
Common steps
- Formulate a null hypothesis and set significance level
- Gather data
- Conduct descriptive statistics
- Conduct test (=inferential) statistics
- Accept or reject the null hypothesis
Statistical error
- type II error worse than type I error
- if null rejected and true = type I error
- if null rejected and false = no error
- if null accepted and true = no error
- if null accepted and false = type II error
- alpha level (=significance level): the probability of making the incorrect decision when null is true
- typical alpha value: 0.05 = 5%
Designing a Controlled Experiment
- control group: a group used as a standard comparison
- experimental group: a group exposed to one experimental variable
- replicates: repetition of an experiment
(NOT all experiments are controlled studies)
