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PIT_PIT [208]
3 years ago
5

What is the slope for (−5,−10) and (−1,5) A 15/4 B - 4/15 C -15/4 D 4/15

Mathematics
1 answer:
bagirrra123 [75]3 years ago
6 0

Answer:

The correct answer would be A. 15/4.

Step-by-step explanation:

Slope is equal to the change in <em>y </em>over the change in x<em>, </em>or rise over run.

m = change in y/change in x

The change in x is equal to the difference in x-coordinates (also called run),  and the change in y is equal to the difference in y-coordinates (also called rise).

m = y2 - y1/x2 - x1

Substitute in the values of x and y into the equation to find the slope.

m = 5 - (- 10)/- 1 - (- 5)

Simplify.

m = 15/4

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</span><span>f(x) = 2x^2 + 28x – 5
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Hope this answers the question. Have a nice day.
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4 years ago
Use division to find all the whole number ratios equivalent to 168 : 56
VikaD [51]
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3 years ago
Write 710,200 in word form
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Answer:

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Step-by-step explanation:


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Read 2 more answers
A coffee machine dispenses normally distributed amounts of coffee with a mean of 12 ounces and a standard deviation of 0.2 ounce
NemiM [27]

Answer:

0.9332 = 93.32% probability that the mean of the sample will be less than 12.1 ounces.

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 z-score 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 p-value, 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.

Mean of 12 ounces and a standard deviation of 0.2 ounces.

This means that \mu = 12, \sigma = 0.2

Sample of 9:

This means that n = 9, s = \frac{0.2}{\sqrt{9}}

Find the probability that the mean of the sample will be less than 12.1 ounces.

This is the pvalue of Z when X = 12.1. So

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

By the Central Limit Theorem

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

Z = \frac{12.1 - 12}{\frac{0.2}{\sqrt{9}}}

Z = 1.5

Z = 1.5 has a pvalue of 0.9332

0.9332 = 93.32% probability that the mean of the sample will be less than 12.1 ounces.

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Answer:

It will have 3 roots

The number of roots in an equation equals the highest power of that equation.

Step-by-step explanation:

3 0
3 years ago
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