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liberstina [14]
3 years ago
12

Is it possible for a simple, connected graph that has n vertices all of different degrees? Explain why or why not.

Mathematics
1 answer:
ryzh [129]3 years ago
8 0

Answer:

It isn't possible.

Step-by-step explanation:

Let G be a graph with n vertices. There are n possible degrees: 0,1,...,n-1.

Observe that a graph can not contain a vertice with degree n-1 and a vertice with degree 0 because if one of the vertices has degree n-1 means that this vertice is adjacent to all others vertices, then the other vertices has at least degree 1.

Then there are n vertices and n-1 possible degrees. By the pigeon principle there are two vertices that have the same degree.

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Answer:

Correct option is (d): Neither X nor Y can be well-approximated by a normal random variable.

Step-by-step explanation:

The sample size of males having color-blindness is, n (X) = 20.

The sample size of females having color-blindness is, n (Y) = 40.

The proportion of males that suffer from color-blindness is, P (X) = 0.08.

The proportion of females that suffer from color-blindness is, P (Y) = 0.01.

Now both the random variables <em>X</em> and <em>Y</em> follows a Binomial distribution,

X\sim Bin(20, 0.08)\\Y\sim Bin(40, 0.01)

A normal distribution is used to approximate the binomial distribution if the sample is large, i.e <em>n</em> ≥ 30 and the probability of success is very close to 0.50.

Also if <em>np</em> ≥ 10 and <em>n</em> (1 - <em>p</em>) ≥ 10, the binomial distribution can be approximated by the normal distribution.

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np=20\times0.08=1.610

In this case neither <em>n</em> > 30 nor <em>p</em> is close to 0.50.

And <em>np</em> < 10.

Thus, the random variable <em>X</em> cannot be approximated by the normal distribution.

<u>For the sample of men (Y):</u>

np=40\times0.01=0.410

In this case <em>n</em> > 30 but <em>p</em> is not close to 0.50.

And <em>np</em> < 10.

Thus, the random variable <em>Y</em> cannot be approximated by the normal distribution.

Thus, both the random variables cannot be approximated by the normal distribution.

The correct option is (d).

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