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vivado [14]
3 years ago
12

What is the answer to 0.1 * n = 89.9 ?

Mathematics
2 answers:
MrRissso [65]3 years ago
4 0
Divide both sides of the equation by 0.1 which leaves you with
n = 89.9/0.1 = 899

Nadusha1986 [10]3 years ago
3 0
The Answer to this question is N=899
How? Let's solve your equation step by step.

0.1n=89.9

Step 1: divide both sides by 0.1.


0.1n = 89.9
0.1      0.1

so 89.9/0.1 we get

n=899

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Assume that a randomly selected subject is given a bone density test. Those test scores are normally distributed with a mean of
jarptica [38.1K]

Answer:

The "probability that a given score is less than negative 0.84" is  \\ P(z.

Step-by-step explanation:

From the question, we have:

  • The random variable is <em>normally distributed</em> according to a <em>standard normal distribution</em>, that is, a normal distribution with \\ \mu = 0 and \\ \sigma = 1.
  • We are provided with a <em>z-score</em> of -0.84 or \\ z = -0.84.

Preliminaries

A z-score is a standardized value, i.e., one that we can obtain using the next formula:

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

Where

  • <em>x</em> is the <em>raw value</em> coming from a normal distribution that we want to standardize.
  • And we already know that \\ \mu and \\ \sigma are the mean and the standard deviation, respectively, of the <em>normal distribution</em>.

A <em>z-score</em> represents the <em>distance</em> from \\ \mu in <em>standard deviations</em> units. When the value for z is <em>negative</em>, it "tells us" that the raw score is <em>below</em> \\ \mu. Conversely, when the z-score is <em>positive</em>, the standardized raw score, <em>x</em>, is <em>above</em> the mean, \\ \mu.

Solving the question

We already know that \\ z = -0.84 or that the standardized value for a raw score, <em>x</em>, is <em>below</em> \\ \mu in <em>0.84 standard deviations</em>.

The values for probabilities of the <em>standard normal distribution</em> are tabulated in the <em>standard normal table, </em>which is available in Statistics books or on the Internet and is generally in <em>cumulative probabilities</em> from <em>negative infinity</em>, - \\ \infty, to the z-score of interest.

Well, to solve the question, we need to consult the <em>standard normal table </em>for \\ z = -0.84. For this:

  • Find the <em>cumulative standard normal table.</em>
  • In the first column of the table, use -0.8 as an entry.
  • Then, using the first row of the table, find -0.04 (which determines the second decimal place for the z-score.)
  • The intersection of these two numbers "gives us" the cumulative probability for z or \\ P(z.

Therefore, we obtain \\ P(z for this z-score, or a slightly more than 20% (20.045%) for the "probability that a given score is less than negative 0.84".

This represent the area under the <em>standard normal distribution</em>, \\ N(0,1), at the <em>left</em> of <em>z = -0.84</em>.

To "draw a sketch of the region", we need to draw a normal distribution <em>(symmetrical bell-shaped distribution)</em>, with mean that equals 0 at the middle of the distribution, \\ \mu = 0, and a standard deviation that equals 1, \\ \sigma = 1.

Then, divide the abscissas axis (horizontal axis) into <em>equal parts</em> of <em>one standard deviation</em> from the mean to the left (negative z-scores), and from the mean to the right (positive z-scores).  

Find the place where z = -0.84 (i.e, below the mean and near to negative one standard deviation, \\ -\sigma, from it). All the area to the left of this value must be shaded because it represents \\ P(z and that is it.

The below graph shows the shaded area (in blue) for \\ P(z for \\ N(0,1).

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Triangle JKL is transformed to create triangle J'K'L'. The angles in both triangles are shown.
Viefleur [7K]

The correct statement is AngleL = 25° AngleL' = 25°.

We have given that,

Triangle JKL is transformed to create triangle J'K'L'.

We have to choose the correct option.

<h3>What is the information about the transformed triangle?</h3>

The following information should be considered:

In a rigid transformation, the image & pre-image are congruent.

Reflection, translation, and rotation are rigid transformations.

In a non-rigid transformation, the image and pre-image are similar.

Dilation is a non rigid transformation.

In a rigid or nonrigid transformation, the corresponding angles are the same.

If the corresponding sides are the same, then it is a rigid transformation.

If the corresponding sides are proportional, then it is a nonrigid transformation.

It can be a rigid or a nonrigid transformation based on whether the corresponding side lengths have the same measures.

Therefore option 3 is correct.

To learn more transformation of the triangle visit:

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