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RoseWind [281]
3 years ago
11

Which example illustrates the distributive property? 4 + 5 = 5 + 4 3(x + 4) = 3x + 12 5 * 1 = 5 4 + (5 + 6) = (4 + 5) + 6

Mathematics
2 answers:
oksian1 [2.3K]3 years ago
8 0
The answer is 4+5=5+4
Paul [167]3 years ago
7 0
Just use google look up "distributive property
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3 years ago
Solve for P:<br><br> 9(p−4)=−18<br><br> Please Explain
vekshin1

Answer:

<em>p</em> = 2

Step-by-step explanation:

Happy to help.

When we have numbers in parenthesis, we generally want to deal with those first. However, we can hit a rough patch when a variable is in there. Consider this:

2(3 + 4) = 2(7), or 14.

But, the two can also be distributed into both numbers in the parenthesis, like this:

2(3 + 4) = 2*3 + 2*4

That leaves us with the same answer—14! We can apply this to a variable, and that will help us figure out 9(<em>p</em> - 4), or the left side of your equation you presented.

9(<em>p</em> - 4) = -18

9*<em>p</em> - 9*4 = -18

9<em>p</em> - 36 = -18

Add 36 on both sides to isolate the variable (in this case, <em>p)</em>

9<em>p</em> = -18 + 36

You can also write it like this; 9<em>p</em> = 36 - 18

9<em>p</em> = 18

Divide 9 to isolate <em>p</em>

<em>p</em> = 2

So, we would get (<em>p</em> = 2). Make sure to practice a few more questions like these to really get the hang of it—you'll be using this a lot in the future!

Good luck!

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What's the value of x when f(x)=58
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Infinite, because essentially the graph is going to have a horizontal line because f(x)=58/y=58 just means that the y will remain on 58 but the x can have whatever value.
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Answer:

a) 99% of the sample means will fall between 0.933 and 0.941.

b) By the Central Limit Theorem, approximately normal, with mean 0.937 and standard deviation 0.0015.

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 zscore 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 pvalue, 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.

(a) If the true mean is 0.9370 with a standard deviation of 0.0090 within what interval will 99% of the sample means fail?

Samples of 34 means that n = 34

We have that \mu = 0.937, \sigma = 0.009

By the Central Limit Theorem, s = \frac{0.009}{\sqrt{34}} = 0.0015

Within what interval will 99% of the sample means fail?

Between the (100-99)/2 = 0.5th percentile and the (100+99)/2 = 99.5th percentile.

0.5th percentile:

X when Z has a pvalue of 0.005. So X when Z = -2.575.

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

By the Central Limit Theorem

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

-2.575 = \frac{X - 0.937}{0.0015}

X - 0.937 = -2.575*0.0015

X = 0.933

99.5th percentile:

X when Z has a pvalue of 0.995. So X when Z = 2.575.

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

2.575 = \frac{X - 0.937}{0.0015}

X - 0.937 = 2.575*0.0015

X = 0.941

99% of the sample means will fall between 0.933 and 0.941.

(b) If the true mean 0.9370 with a standard deviation of 0.0090, what is the sampling distribution of ¯X?

By the Central Limit Theorem, approximately normal, with mean 0.937 and standard deviation 0.0015.

6 0
3 years ago
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