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Negative binomial parameters-what does it mean?

I’m reading a survey paper on data on DNA pooling and I came across a section where they state that

The number of times a given locus was affected, $M$, is a negative binomial random variable, with parameter $m$.

I can’t work out what this means. The text then goes on to say

Here we are interested in $M$ and it is measured on the logarithmic scale. The time at which $M$ was measured can be seen as a Poisson random variable, $T$, with parameter $\mu$.

I know that $\mu$ is the mean of $T$. I’ve read that Poisson is a discrete probability density, $P(T) = \frac{\lambda^T}{T!}\exp(-\lambda)$ which means that the mean is the parameter $1/\lambda$. I think my trouble is working out what the parameter $m$ for the negative binomial should be?

A:

A negative binomial distribution is a discrete, discrete-time stochastic process.
Here is a picture of the negative binomial distribution.

Or, if we put a vector of random variables into an (n,m) rectangular array.

So, a negative

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Clear difference between first and second-rank attributes and their implied power

This question originally had a very slight related answer (I think) in the tags; but this seems an easy question to ask.
I have seen online that many singular n-grams (e.g. “eat”) are second-rank. A classic example is “train”: on the spectrum, first-rank words are always verbs (train is a noun, not a verb), and second-rank verbs are almost always pluralized (words like “train”).
I am wondering why.
In English, “eat” is a second-rank word. So second-rank words, in general, have more power than first-rank words.
But then, in vocabulary lists, first-rank words get more power than second-rank words. For example, here is a list of 10 most frequently used words by count:

good (7,497)
eat (7,412)
go (6,580)
etc.

Why do first-rank words get less power than second-rank words in online lists, but more power than second-rank words in printed lists? And more generally, what is the deal with how singular n-grams are mapped to ranks?

A:

The implicit assumption made here is that the ranks of
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