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emmasim [6.3K]
3 years ago
15

What is the distance between the points (2, 5) and (5, 7)?

Mathematics
2 answers:
butalik [34]3 years ago
8 0
D^2=x^2+y^2

d^2=(dx)^2+(dy)^2

d^2=(5-2)^2+(7-5)^2

d^2=3^2+2^2

d^2=9+4

d^2=13

d=√13
tangare [24]3 years ago
7 0

Answer:

The distance between two points  (2, 5) and (5, 7) is √13

Step-by-step explanation:

Given: Points (2, 5) and (5, 7)            

We have to find the distance between the given points (2, 5) and (5, 7)

Consider the given points (2, 5) and (5, 7)

Distance between two points is calculated using formula

D=\sqrt{\left(x_2-x_1\right)^2+\left(y_2-y_1\right)^2}

\left(x_1,\:y_1\right)=(2,5),\:\left(x_2,\:y_2\right)=(5,7)

Thus, D=\sqrt{\left(5-2\right)^2+\left(7-5\right)^2}=\sqrt{9+4}=\sqrt{13}

Thus, The distance between two points  (2, 5) and (5, 7) is √13

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baherus [9]

Answer:

The mean is 9.65 ohms and the standard deviation is 0.2742 ohms.

Step-by-step explanation:

Problems of normally distributed samples are 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.

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This means that when X = 10.634, Z has a pvalue of 1-0.1 = 0.9. So when X = 10.634, Z = 1.28.

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

1.28 = \frac{10.634 - \mu}{\sigma}

10.634 - \mu = 1.28\sigma

\mu = 10.634 - 1.28\sigma

5% having a resistance smaller than 9.7565 ohms.

This means that when X = 9.7565, Z has a pvalue of 0.05. So when X = 9.7565, Z = -1.96.

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

-1.96 = \frac{9.7565 - \mu}{\sigma}

9.7565 - \mu = -1.96\sigma

\mu = 9.7565 + 1.96\sigma

We also have that:

\mu = 10.634 - 1.28\sigma

So

10.634 - 1.28\sigma = 9.7565 + 1.96\sigma

1.96\sigma + 1.28\sigma = 10.645 - 9.7565

3.24\sigma = 0.8885

\sigma = \frac{0.8885}{3.24}

\sigma = 0.2742

The mean is

\mu = 10.634 - 1.28\sigma = 10 - 1.28*0.2742 = 9.65

The mean is 9.65 ohms and the standard deviation is 0.2742 ohms.

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