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Delvig [45]
3 years ago
14

Help please, my brain stopped working and my assignment is due by midnight

Mathematics
2 answers:
Marizza181 [45]3 years ago
3 0
The correct answer is x= -6 let me know if you want to know how I got that or if you needed to know if it is no solution/ infinite/etc..
Andrews [41]3 years ago
3 0

Answer:

<h2>x = -18</h2>

Step-by-step explanation:

<u>2x</u> - 1 = <u>3x</u> + <u> 1 </u>

3           4      2

<u>2x</u> -  <u>3x</u> = 1 +  <u> 1 </u>

3       4            2

_  <u> 1x  </u>  =  1.5

    12

-1x = 12 (1.5)

x = 18 / -1

x = -18

<u>proof:</u>

<u>2(-18)</u> - 1 = <u>3(-18)</u> + <u> 1 </u>

   3              4         2

-12 - 1 = -13.5 + 0.5

-13 = -13 --ok

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What is a conversion factor that you an use to convert gallons to pints?how did you find it?
Mariana [72]
Volume unit conversion. 1 gallon = 8 pints.
3 0
3 years ago
Write an expression that equals 56. Include an exponent.
Troyanec [42]

There are many possibilities. An example is 1^{1} + 55 = 56.

6 0
3 years ago
An obtuse triangle with area 12 has two sides of lengths 4 and 10. Find the length of the third side. (There are two answers.) (
mart [117]
This question can be solved using the Herons equation where 
A = SQRT [s*(s-a)*(s-b)*(s-c)]

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a, b and c are the sides of the triangle

s = (a+b+c)/2

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3 0
3 years ago
Test scores of the student in a school are normally distributed mean 85 standard deviation 3 points. What's the probability that
Mrrafil [7]

Answer:

The probability that a random selected student score is greater than 76 is \\ P(x>76) = 0.99865.

Step-by-step explanation:

The Normally distributed data are described by the normal distribution. This distribution is determined by two <em>parameters</em>, the <em>population mean</em> \\ \mu and the <em>population standard deviation</em> \\ \sigma.

To determine probabilities for the normal distribution, we can use <em>the standard normal distribution</em>, whose parameters' values are \\ \mu = 0 and \\ \sigma = 1. However, we need to "transform" the raw score, in this case <em>x</em> = 76, to a z-score. To achieve this we use the next formula:

\\ z = \frac{x - \mu}{\sigma} [1]

And for the latter, we have all the required information to obtain <em>z</em>. With this, we obtain a value that represent the distance from the population mean in standard deviations units.

<h3>The probability that a randomly selected student score is greater than 76</h3>

To obtain this probability, we can proceed as follows:

First: obtain the z-score for the raw score x = 76.

We know that:

\\ \mu = 85

\\ \sigma = 3

\\ x = 76

From equation [1], we have:

\\ z = \frac{76 - 85}{3}

Then

\\ z = \frac{-9}{3}

\\ z = -3

Second: Interpretation of the previous result.

In this case, the value is <em>three</em> (3) <em>standard deviations</em> <em>below</em> the population mean. In other words, the standard value for x = 76 is z = -3. So, we need to find P(x>76) or P(x>-3).

With this value of \\ z = -3, we can obtain this probability consulting <em>the cumulative standard normal distribution, </em>available in any Statistics book or on the internet.

Third: Determination of the probability P(x>76) or P(x>-3).

Most of the time, the values for the <em>cumulative standard normal distribution</em> are for positive values of z. Fortunately, since the normal distributions are <em>symmetrical</em>, we can find the probability of a negative z having into account that (for this case):

\\ P(z>-3) = 1 - P(z>3) = P(z

Then

Consulting a <em>cumulative standard normal table</em>, we have that the cumulative probability for a value below than three (3) standard deviations is:

\\ P(z

Thus, "the probability that a random selected student score is greater than 76" for this case (that is, \\ \mu = 85 and \\ \sigma = 3) is \\ P(x>76) = P(z>-3) = P(z.

As a conclusion, more than 99.865% of the values of this distribution are above (greater than) x = 76.

<em>We can see below a graph showing this probability.</em>

As a complement note, we can also say that:

\\ P(z3)

\\ P(z3)

Which is the case for the probability below z = -3 [P(z<-3)], a very low probability (and a very small area at the left of the distribution).

5 0
3 years ago
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