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kakasveta [241]
3 years ago
10

Plz help me. Simplify:

Mathematics
2 answers:
alekssr [168]3 years ago
4 0

Answer:

-14/1-5x

Step-by-step explanation:

Serga [27]3 years ago
4 0

Answer:

  -14

D   ------------------  where    x≠0  x≠1/5

     (1-5x)  

Step-by-step explanation:

-14x^3

------------------

x^3 -5x^4

Factor an x^3 from the denominator

-14x^3

------------------

x^3 (1-5x)  

To determine the limits  we use the zero product property on the denominator

x≠0  or 1-5x≠0

  x≠0  x≠1/5

We can cancel the x^3 term in both the top and the denominator

-14

------------------  where    x≠0  x≠1/5

(1-5x)  

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I need help solving this
ValentinkaMS [17]
11, 13, and 16. sorry if im wrong, and i hope this helps.
5 0
3 years ago
A public health organization reports that 40%of baby boys 6-8 months old in the United
Sveta_85 [38]

Using the binomial distribution, the probabilities are given as follows:

  • 0.3675 = 36.75% probability that more than 4 weigh more than 20 pounds.
  • 0.1673 = 16.73% probability that fewer than 3 weigh more than 20 pounds.
  • Since P(X > 7) < 0.05, it would be unusual if more than 7 of them weigh more than 20 pounds.

<h3>What is the binomial distribution formula?</h3>

The formula is:

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

C_{n,x} = \frac{n!}{x!(n-x)!}

The parameters are:

  • x is the number of successes.
  • n is the number of trials.
  • p is the probability of a success on a single trial.

The values of the parameters for this problem are:

n = 10, p = 0.4.

The probability that more than 4 weigh more than 20 pounds is:

P(X > 4) = 1 - P(X \leq 4)

In which:

P(X \leq 4) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3) + P(X = 4)

Then:

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

P(X = 0) = C_{10,0}.(0.4)^{0}.(0.6)^{10} = 0.0061

P(X = 1) = C_{10,1}.(0.4)^{1}.(0.6)^{9} = 0.0403

P(X = 2) = C_{10,2}.(0.4)^{2}.(0.6)^{8} = 0.1209

P(X = 3) = C_{10,3}.(0.4)^{3}.(0.6)^{7} = 0.2150

P(X = 4) = C_{10,4}.(0.4)^{4}.(0.6)^{6} = 0.2502

Hence:

P(X \leq 4) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3) + P(X = 4) = 0.0061 + 0.0403 + 0.1209 + 0.2150 + 0.2502 = 0.6325

P(X > 4) = 1 - P(X \leq 4) = 1 - 0.6325 = 0.3675

0.3675 = 36.75% probability that more than 4 weigh more than 20 pounds.

The probability that fewer than 3 weigh more than 20 pounds is:

P(X < 3) = P(X = 0) + P(X = 1) + P(X = 2) = 0.0061 + 0.0403 + 0.1209 = 0.1673

0.1673 = 16.73% probability that fewer than 3 weigh more than 20 pounds.

For more than 7, the probability is:

P(X > 7) = P(X = 8) + P(X = 9) + P(X = 10)

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

P(X = 8) = C_{10,8}.(0.4)^{8}.(0.6)^{2} = 0.0106

P(X = 9) = C_{10,9}.(0.4)^{9}.(0.6)^{1} = 0.0016

P(X = 10) = C_{10,10}.(0.4)^{10}.(0.6)^{0} = 0.0001

Since P(X > 7) < 0.05, it would be unusual if more than 7 of them weigh more than 20 pounds.

More can be learned about the binomial distribution at brainly.com/question/24863377

#SPJ1

4 0
2 years ago
The graph shows y as a function of x
nirvana33 [79]
I'm guessing Q lol. I hope that's helpful.
3 0
3 years ago
The population standard deviation for the temperature of beers found in Scooter's Tavern is 0.26 degrees. If we want to be 90% c
siniylev [52]

Answer:

19 beers must be sampled.

Step-by-step explanation:

We have that to find our \alpha level, that is the subtraction of 1 by the confidence interval divided by 2. So:

\alpha = \frac{1 - 0.9}{2} = 0.05

Now, we have to find z in the Z-table as such z has a p-value of 1 - \alpha.

That is z with a pvalue of 1 - 0.05 = 0.95, so Z = 1.645.

Now, find the margin of error M as such

M = z\frac{\sigma}{\sqrt{n}}

In which \sigma is the standard deviation of the population and n is the size of the sample.

The population standard deviation for the temperature of beers found in Scooter's Tavern is 0.26 degrees.

This means that \sigma = 0.26

If we want to be 90% confident that the sample mean beer temperature is within 0.1 degrees of the true mean temperature, how many beers must we sample?

This is n for which M = 0.1. So

M = z\frac{\sigma}{\sqrt{n}}

0.1 = 1.645\frac{0.26}{\sqrt{n}}

0.1\sqrt{n} = 1.645*0.26

\sqrt{n} = \frac{1.645*0.26}{0.1}

(\sqrt{n})^2 = (\frac{1.645*0.26}{0.1})^2

n = 18.3

Rounding up:

19 beers must be sampled.

7 0
3 years ago
Response will be saved automatically.
Charra [1.4K]

Answer:

443.28

Step-by-step explanation:

Subtract 42.24 from 570.3 three times.

3 0
3 years ago
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