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uysha [10]
4 years ago
13

If a third point is drawn 5 units to the left of (3, 5), in order to form the base of a right triangle, what are the coordinates

of the third point? (5, -3) (-2, 5) (0, 5) (3, 0)
Mathematics
1 answer:
katrin [286]4 years ago
3 0

Answer:

the second answer

Step-by-step explanation:

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Slope of a line

m = \frac{\text{rise}}{\text{run}} = \frac{y_2 - y_1}{x_2 - x_1}

m = slope

(x_1, y_1) = coordinates of first point in the line

(x_2, y_2) = coordinates of second point in the line

How do I find the slope of the line?

The slope equals the rise divided by the run: . You can determine the slope of a line from its graph by looking at the rise and run. One characteristic of a line is that its slope is constant all the way along it. So, you can choose any 2 points along the graph of the line to figure out the slope.

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Step-by-step explanation:

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What is the probability that a randomly selected member of a normally distributed population will lie more than 1.8 standard dev
Helen [10]

Answer:

P(X> \mu +1.8\sigma)=P(\frac{X-\mu}{\sigma}>\frac{\mu +1.8\sigma-\mu}{\sigma})=P(Z>1.8)

And we can find this probability using the complement rule:

P(z>1.8)=1-P(z

And using the normal standard distirbution table or excel we got:

P(z>1.8)=1-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 variable if interest of a population, and for this case we know the distribution for X is given by:

X \sim N(\mu,\sigma)  

We are interested on this probability

P(X>\mu +1.8 \sigma)

And the best way to solve this problem is using the normal standard distribution and the z score given by:

z=\frac{x-\mu}{\sigma}

If we apply this formula to our probability we got this:

P(X> \mu +1.8\sigma)=P(\frac{X-\mu}{\sigma}>\frac{\mu +1.8\sigma-\mu}{\sigma})=P(Z>1.8)

And we can find this probability using the complement rule:

P(z>1.8)=1-P(z

And using the normal standard distirbution table or excel we got:

P(z>1.8)=1-P(z

5 0
4 years ago
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