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tatiyna
3 years ago
10

What is the total number of relative maximum and minimum points of the function whose derivative for all x is given by f ‘ (x) =

x(x – 3)^2 (x + 1)^4 ?
Mathematics
1 answer:
Alexeev081 [22]3 years ago
8 0

Answer:

There are in total 3 maximum and minimum points of f(x)

Step-by-step explanation:

To find the number of stationary points (maximum and minimum points) in any function (f(x)), we need to find for what values of x does the derivative of f(x) equal to 0.

mathematically, for how many values of x does f'(x) = 0

f'(x) = x(x-3)^2(x+1)^4

0 = x(x-3)^2(x+1)^4

since the factors can be separately solved we can write

0 = x, 0 = (x-3)^2, 0 = (x+1)^4

x= 0, \sqrt{(x-3)^2} = \sqrt{0}, \sqrt{(x+1)^4}=\sqrt{0}

x=0, (x-3)=0, (x+1)=0

x = 0, x = 3, x = -1

Since there are 3 answers of x for which f'(x) = 0, we can say that the there are a total of 3 stationary (maximum or minimum) points in f(x).

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Answer:

C. $0.19/ounce

Step-by-step explanation:

We know that 16 ounces = 1 pound but we have 5 pounds,

So, we do 5 times 16.

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We get our answer:

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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

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.

Step-by-step explanation:

Previous concepts

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.

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Step-by-step explanation:

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