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3 years ago

Help <3 ;3

2 answers:

8 0

Hello,

Rational numbers are numbers that can be represented by fractions that consist of integers.

In this case, B. -7/3 is already a fraction that consists of integers, so it is a rational number.
C. square 3 is = $3^{2}$ = 9, which can be represented by 9/1, so it is also a rational number.

A and D are incorrect as they cannot be represented by fractions that consist of integers.

The answers are B and C.

Hope this helps!

diamong [38]3 years ago

5 0

Answer:

A. 2.77777...

$B. -\frac{7}{3}$

Step-by-step explanation:

A rational number can be written in the form $\frac{a}{b}$ ,where $b\ne 0$ and $a,b$ are integers.

The number $2.77777...$ can be rewritten as $\frac{25}{9}$ .

This is a rational number.

$-\frac{7}{3}$ is also a rational number.

$\sqrt{3}=1.73205080...$

No recurring pattern so it is an irrational number

$2.7182818459....$ also has no recurring pattern. This is also an irrational number.

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Shalnov [3]

Answer:

a) $P(X=12)=(25C12)(0.6)^{12} (1-0.6)^{25-12}=0.0760$

b) $P(X>17) = P(X=18) +....+P(X=25)$

And we can use the following excel code: "=1-BINOM.DIST(17;25,0.6,TRUE)"

And we got:

$P(X>17) = P(X=18) +....+P(X=25)= 0.154$

c) $P(X$

And using the following excel code we got: "=BINOM.DIST(7,25,0.6,TRUE)"

And we got:

$P(X$

Step-by-step explanation:

Previous concepts

A Bernoulli trial is "a random experiment with exactly two possible outcomes, "success" and "failure", in which the probability of success is the same every time the experiment is conducted". And this experiment is a particular case of the binomial experiment.

The binomial distribution is a "DISCRETE probability distribution that summarizes the probability that a value will take one of two independent values under a given set of parameters. The assumptions for the binomial distribution are that there is only one outcome for each trial, each trial has the same probability of success, and each trial is mutually exclusive, or independent of each other".

The probability mass function for the Binomial distribution is given as:

$P(X)=(nCx)(p)^x (1-p)^{n-x}$

Where (nCx) means combinatory and it's given by this formula:

$nCx=\frac{n!}{(n-x)! x!}$

The complement rule is a theorem that provides a connection between the probability of an event and the probability of the complement of the event. Lat A the event of interest and A' the complement. The rule is defined by: $P(A)+P(A') =1$