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melisa1 [442]
3 years ago
14

Given that x < 5, rewrite 5x - |x - 5| without using absolute value signs.

Mathematics
2 answers:
arsen [322]3 years ago
8 0

For x, x-5, therefore |x-5|=-(x-5)=-x+5

So, for x, 5x-|x-5|=5x-(-x+5)=5x+x-5=6x-5

andriy [413]3 years ago
5 0

So, if we have an arbitrary number under the absolute value, say y, we have |y| to be:

y0 \implies |y| =y

Which in plain english means "If y is less than 0, then the absolute value of y is the negation of y, and if y is greater than 0 then the absolute value of y is y."

So, in our above absolute value expression we would have:

x-5 < 0 \implies |x-5| = -(x-5) \\ x-5>0 \implies |x-5| = x-5

Since we are given x<5, we know that the absolute value actually negates what's encompassed by it so we have:

5x-(-(x-5))=\\ 5x-(-x+5)= 5x+x-5= 6x-5

So our expression without the absolute value signs is simply 6x-5.

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Simplify (3w^2-7w+6)+(-5w^2+2w+1)
leva [86]

Answer:

-2w^2 - 5w + 7

Step-by-step explanation:

Just the values with the same powers of w

(3w^2-5w^2)+(-7w+2w)+(6+1)

-2w^2 - 5w + 7

5 0
2 years ago
What is the missing numbers in this sequence: , 7, 5, 3, , -1
matrenka [14]

Answer:

1 is the missing number.

Step-by-step explanation:

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3 years ago
Assume that P(E) = 0.471 and P(F) = 0.595. If E and F are independent, find P(E and F)
dsp73

The value of the probability P(E and F) is 0.2802

<h3>Independent probability</h3>

Events are known to be independent if the occurrence of one does not affect the other.

Given the following parameters

P (E) =0.471

P(F) = 0.595

If E and F are independent, then;

P(E and F) = P(E)P(F)

P(E and F)  = 0.471 * 0.595
P(E and F)  = 0.2802

Hence the value of the probability P(E and F) is 0.2802

Learn more on independent events here: brainly.com/question/1374659

#SPJ1

8 0
2 years ago
What is the reciprocal of 4.5? And after I get the reciprocal how did they get 2 over 9 for the answer?
djverab [1.8K]
So 4.5 is equal to 4 and 1/2 
u can convert that to 9/2
then to get the reciprocal you flip the denominator and numerator
this gives u 2/9
3 0
3 years ago
The Office of Student Services at a large western state university maintains information on the study habits of its full-time st
Vera_Pavlovna [14]

Answer:

0.8254 = 82.54% probability that the mean of this sample is between 19.25 hours and 21.0 hours

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 estabilishes 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 20 hours, standard deviation of 6:

This means that \mu = 20, \sigma = 6

Sample of 150:

This means that n = 150, s = \frac{6}{\sqrt{150}}

What is the probability that the mean of this sample is between 19.25 hours and 21.0 hours?

This is the p-value of Z when X = 21 subtracted by the p-value of Z when X = 19.5. So

X = 21

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

By the Central Limit Theorem

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

Z = \frac{21 - 20}{\frac{6}{\sqrt{150}}}

Z = 2.04

Z = 2.04 has a p-value of 0.9793

X = 19.5

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

Z = \frac{19.5 - 20}{\frac{6}{\sqrt{150}}}

Z = -1.02

Z = -1.02 has a p-value of 0.1539

0.9793 - 0.1539 = 0.8254

0.8254 = 82.54% probability that the mean of this sample is between 19.25 hours and 21.0 hours

3 0
3 years ago
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