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Vsevolod [243]
3 years ago
14

Describe the distributive property of R in your own words? Please help

Mathematics
1 answer:
Natasha_Volkova [10]3 years ago
8 0

Answer:

Definition: The distributive property lets you multiply a sum by multiplying each addend separately and then add the products. ... Consider the first example, the distributive property lets you "distribute" the 5 to both the 'x' and the '2'.

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Solving systems by elimination <br> 9x+3y=-3 <br> 2x-3y=-8
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Answer:

Solve for the first variable in one of the equations, then substitute the result into the other equation.

x

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1

Step-by-step explanation:

5 0
3 years ago
Could anyone help me with this?
Vaselesa [24]

Answer:

Here is your answer with solutions.

7 0
2 years ago
To decrease the impact on the environment, factory chimneys must be high enough to allow pollutants to dissipate over a larger a
Komok [63]

Answer:

The probability hat the sample mean height for the 40 chimneys is greater than 102 meters is 0.1469.

Step-by-step explanation:

Let the random variable <em>X</em> be defined as the height of chimneys in factories.

The mean height is, <em>μ</em> = 100 meters.

The standard deviation of heights is, <em>σ</em> = 12 meters.

It is provided that a random sample of <em>n</em> = 40 chimney heights is obtained.

According to the Central Limit Theorem if we have an unknown population with mean <em>μ</em> and standard deviation <em>σ</em> and appropriately huge random samples (<em>n</em> > 30) are selected from the population with replacement, then the distribution of the sample means will be approximately normally distributed.

Then, the mean of the distribution of sample means is given by,

\mu_{\bar x}=\mu

And the standard deviation of the distribution of sample means is given by,

\sigma_{\bar x}=\frac{\sigma}{\sqrt{n}}

Since the sample selected is quite large, i.e. <em>n</em> = 40 > 30, the central limit theorem can be used to approximate the sampling distribution of sample mean heights of chimneys.

\bar X\sim N(\mu_{\bar x},\ \sigma^{2}_{\bar x})

Compute the probability hat the sample mean height for the 40 chimneys is greater than 102 meters as follows:

P(\bar X>102)=P(\frac{\bar X-\mu_{\bar x}}{\sigma_{\bar x}})>\frac{102-100}{12/\sqrt{40}})

                    =P(Z>1.05)\\=1-P(Z

*Use a <em>z</em>-table fr the probability.

Thus, the probability hat the sample mean height for the 40 chimneys is greater than 102 meters is 0.1469.

8 0
3 years ago
Whixh graph shows a plot of the complex number I -2?
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5 0
3 years ago
9d - 5 = 4d + 35<br> find what d equals.
Debora [2.8K]
9d - 5 = 4d + 35

9d (-4d) - 5 (+5) = 4d (-4d) + 35 (+5)

5d = 40

5d/5 = 40/5

d = 8

hope this helps
3 0
3 years ago
Read 2 more answers
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