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laila [671]
2 years ago
5

Factor completely. n² - 5n + 4​

Mathematics
1 answer:
Gnesinka [82]2 years ago
6 0

Answer:

(n-4)(n-1)

Step-by-step explanation:

n2 -5n +4

n2- n - 4n - 4

n(n-1) - 4(n-1)

(n-4)(n-1)

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Please help due tomorrow Fri
ch4aika [34]
5 feet is the answer
3 0
3 years ago
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What is “ f(x) = 2x^2- 32x” in standard form if it has one?
kap26 [50]
Most textbooks interpret standard form of a quadratic function to be as follows:

f(x) = a x^{2}  + bx + c

In the function f(x) = 2 x^{2}  - 32x , notice we do not have a value for "c". Just place a "0" in for the c and you have standard form.

the criteria for standard form:
1. All like terms are combined
2. Degree must drop from left to right
3. The leading coefficient cannot be equal to zero.
6 0
3 years ago
A manufacturer knows that their items have a normally distributed length, with a mean of 15.4 inches, and standard deviation of
Masteriza [31]

Answer:

0.9452 = 94.52% probability that their mean length is less than 16.8 inches.

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal Probability Distribution:

Problems of normal distributions can be solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the z-score of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

Mean of 15.4 inches, and standard deviation of 3.5 inches.

This means that \mu = 15.4, \sigma = 3.5

16 items are chosen at random

This means that n = 16, s = \frac{3.5}{\sqrt{16}} = 0.875

What is the probability that their mean length is less than 16.8 inches?

This is the p-value of Z when X = 16.8. So

Z = \frac{X - \mu}{\sigma}

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{16.8 - 15.4}{0.875}

Z = 1.6

Z = 1.6 has a p-value of 0.9452.

0.9452 = 94.52% probability that their mean length is less than 16.8 inches.

5 0
3 years ago
What is the value of fraction 1 over 3x3 + 5.4y, when x = 3 and y = 2? 13.8 16.8 19.8 28.8
Bond [772]
The answer is 16.8. Tell me if I'm right
7 0
3 years ago
Which of the following are situations that can be modeled with a quadratic function? Select all that apply.
Lina20 [59]

Answer:

Option 2 and 5 are correct.

Step-by-step explanation:

We need to tell which one of them is quadratic function.

Option 1 is exponential decay so, it is not quadratic.

Option 2 is quadratic because the diver will take the parabolic shape when jumps.

Option 3 is not quadratic.Option 4 is not quadratic it is linear.

Option 4 is again exponential not quadratic.

Option 5 is quadratic because it takes the parabolic shape again.


4 0
3 years ago
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