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yulyashka [42]
3 years ago
8

Tributive Propertyeach of the following. Show for what valx - 2(x - 2) =X​

Mathematics
1 answer:
levacccp [35]3 years ago
4 0

Answer:

Step-by-step explanation:

Subtraction is not commutative. For example, 4 − 7 does not have the same difference as 7 − 4. The − sign here means subtraction.

 

However, recall that 4 − 7 can be rewritten as 4 + (−7), since subtracting a number is the same as adding its opposite. Applying the commutative property for addition here, you can say that 4 + (−7) is the same as (−7) + 4. Notice how this expression is very different than 7 – 4.

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Write the slope-intercept form of the equation of each line given the slope and y-intercept.
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Y = -10X - 5

Step-by-step explanation:

Y = mX + b

m - slope

b - y - intercept.

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15

Step-by-step explanation:

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The length of a line is y centimeters write down an expression, in terms of y, for the length of the line in milimiters
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The heights of baby giraffe are normally distributed with a mean of 63.6 inches and a standard deviation of 2.5 inches. If 100 b
ANEK [815]

Answer:

P(\bar X

And we can solve this using the following z score formula:

z = \frac{\bar X -\mu}{\frac{\sigma}{\sqrt{n}}}

And if we use this formula we got:

z = \frac{63-63.6}{\frac{2.5}{\sqrt{100}}}= -2.4

So we can find this probability equivalently like this:

P( Z

Step-by-step explanation:

Previous concepts

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".  

Solution to the problem

Let X the random variable that represent the heights of a population, and for this case we know the distribution for X is given by:

X \sim N(63.6,2.5)  

Where \mu=63.6 and \sigma=2.5

We select n =100. Since the distribution for X is normal then we know that the distribution for the sample mean \bar X is given by:

\bar X \sim N(\mu, \frac{\sigma}{\sqrt{n}})

We want this probability:

P(\bar X

And we can solve this using the following z score formula:

z = \frac{\bar X -\mu}{\frac{\sigma}{\sqrt{n}}}

And if we use this formula we got:

z = \frac{63-63.6}{\frac{2.5}{\sqrt{100}}}= -2.4

So we can find this probability equivalently like this:

P( Z

4 0
3 years ago
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