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3 years ago

Describe and give examples of the two types of genetic drift

1 answer:

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Of the two pink monkeys in the world – one male, one female – the female dies, ensuring that there will never be a pure-bred pink monkey again.
A random succession of births results in all other hair colors going extinct within a village full of redheaded people.

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What is the purpose of the great green wall

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Which experimental design decision would most likely produce invalid and unreliable results?

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Explanation:

The independent variable determines the value that needs to be calculated or the decision that needs to be made from the observations of the experiment. Hence, experimental design decision would most likely produce invalid and unreliable results when having more than one independent variable.

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4 years ago

Write a paragraph on testing probability

VashaNatasha [74]

Explanation:

Probabilities are described as ratios of favorable event outcome to the total number of event outcomes.

This is written as...

$P (E) =\frac{n(E)}{n(S)} \\$

where...

E= the number of times the event occurs

S= the number of trials

In biology experiments, hypotheses are formed based on research questions, and tested with the use of variables to provide a particular outcome. Statistics allows for testing data for consistency with the hypothesis, while statistical probability testing can be used in experiments to determine a range of outcomes, from genetic inheritance, evolutionary rates to theoretical experimental results.

In these statistical models, probability distributions are functions that give probabilities for certain event outcomes within an experiment (a set of trials). These may be either continuous, taking a value within a range of two numbers; or discrete, which may be either of two specified values. Discrete probability distributions list each value that a random variable may possibly take on.

Further Explanation:

For example, two types of probability distributions are employed in experimental biology:

Binomial distributions, which are discrete distributions, provide probability of a certain number of successful events for x a random variable, in a specific number of trials, n; here, the probability of success of an individual trial is constant at P and only one of two outcomes are possible- this is sampling with replacement.

where...

b(x; n, P)-the probability that an experiment of n trials results in x successes

nCx- the number of combinations of n things at r time

$b(x; n, P) = [ nCx ]* P^{x} * (1-P)^{n-x}\\$

This is often used in determining potential outcomes before data collection.

A type of continuous distribution, the student's t-test, compares standard deviations and means from two sets of samples or groups to check for significant differences between them.

$t= \frac{(x_{1} - x_{2}) }{\sqrt{(\frac{(S_{1}) ^{2} }{n1} }+ (\frac{(S_{2}) ^{2} }{n2 }}$

where...

x1 and s1 are the mean and standard deviation of sample 1 respectively
x2 and s2 are the mean and standard deviation of sample 1 respectively
n1 and n2 are sample sizes in samples 1 and 2 respectively

The null and alternate hypotheses typically theorize the likelihood and significance of certain event outcome probabilities. Critical values of t, along with degrees of freedom are used to determine a range of probable outcomes; probability or p- values along with this range, are used to determine whether either hypothesis is rejected or accepted.

For instance, significant differences between an experimental control and a specific treatment group would show that these occurrences are not due to sampling errors or random chance...

Learn more about calculating probability at brainly.com/question/4021035

Learn more about calculating event probability at brainly.com/question/6649771

#LearnWithBrainly

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3 years ago