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Dvinal [7]
3 years ago
11

Samantha is making flower arrangements. She has 32 roses and 96 daisies. If she wants to make all the arrangements identical and

have no flowers left over, how many daisies will be in each flower arrangement?
Mathematics
1 answer:
-Dominant- [34]3 years ago
7 0

Answer:

3 daisies.

Step-by-step explanation:

Given that,

Samantha has 32 roses and 96 daisies.

She wants to make all the arrangements identical and have no flowers left over. We need to find the no of daisies in each flower arrangement.

For this, we need to first find the HCF of 32 and 96.

The factors of 32 are: 1, 2, 4, 8, 16, 32

The factors of 96 are: 1, 2, 3, 4, 6, 8, 12, 16, 24, 32, 48, 96

HCF = 32

No of daisies = 96/32 = 3

Hence, there are 3 daisies in each flower arrangement.

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You are at a stall at a fair where you have to throw a ball at a target. There are two versions of the game. In the first
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Answer:

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And the probability of loss with the first wersion is 0.729

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And the probability of loss with the first wersion is 0.774

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Step-by-step explanation:

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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".

Solution to the problem

Alternative 1

Let X the random variable of interest, on this case we now that:

X \sim Binom(n=3, p=0.1)

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!}

We can find the probability of loss like this P(X=0) and if we find this probability we got this:

P(X=0)=(3C0)(0.1)^0 (1-0.1)^{3-0}=0.729

And the probability of loss with the first wersion is 0.729

Alternative 2

Let Y the random variable of interest, on this case we now that:

Y \sim Binom(n=5, p=0.05)

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

P(Y)=(nCy)(p)^y (1-p)^{n-y}

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

nCy=\frac{n!}{(n-y)! y!}

We can find the probability of loss like this P(Y=0) and if we find this probability we got this:

P(Y=0)=(5C0)(0.05)^0 (1-0.05)^{5-0}=0.774

And the probability of loss with the first wersion is 0.774

As we can see the best alternative is the first version since the probability of loss is lower than the probability of loss on version 2.

4 0
4 years ago
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