In this question we will do a Biological Classification History Check.
<h3>1. Binomial nomenclature</h3>
Binomial nomenclature or binary nomenclature designates the set of rules that regulate the attribution of scientific names to species of living beings.
<h3>2. Domain</h3>
Is based on molecular phylogeny data. According to Woese, there are three domains: Archaea Domain, Bacteria Domain, and Eukarya Domain.
<h3>3. Both focus on illustrating taxonomic relationships between organisms.</h3>
No, binomial nomenclature is for the purpose of assigning names.
<h3>4. domain, kingdom, phylum only.</h3>
No, the classification is more extensive
<h3>5. juglans nigra</h3>
It is a tree that can reach heights between 20 to 50 m. It is still a monoecious, deciduous and aromatic tree.
Learn more about Binomial nomenclature in brainly.com/question/9837065
Answer:
a. spore
Explanation:
Fungi is a kingdom in which you can fund yeast, mold, and all kind of fungus, microcellular, and monocellular ones.
The way fungi reproduction is through spores that get distributed in a latent way until thy fund its necessary conditions to living.
These spores can create both ways, sexual and asexual.
Plastics clearly constitute an important component of the range of materials used in modern society. Almost all aspects of daily life involve plastics or rubber in some form or the other. ... Owing to their light weight, plastics reduce transportation costs and, therefore, atmospheric carbon dioxide emissions./Plastic is durable and provides protection from contaminants and the elements.
The answer to your question is true
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Bias can happen in sampling. The propensity of a sample statistic to systematically under- or
over-approximate a population is referred to as bias.
To add, in statistics, sampling bias is a bias in
which a sample is collected in such a way that some members of the
intended population are less likely to be included than others.
The following are some types of biases in Statistics:
Selection bias includes individuals being more
likely to be chosen for study than others, biasing
the sample. This can also be termed Berksonian bias
In statistical hypothesis testing, a
test is said to be unbiased if for some alpha level (between 0 and
1), the probability the null is not accepted is less than or equal to the alpha
level for the entire parameter space defined by the null hypothesis, while the
probability the null is rejected is greater than or equal to the alpha level
for the entire criterion space interpreted by the alternate hypothesis.
