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4 years ago

What's the basic geometric term for the part of an angle where two rays begin and go in two different directions?

Mathematics

1 answer:

wlad13 [49]4 years ago

5 0

Answer

B. Vertex

Explanation

A vertex is the meeting point of two rays or lines. It is also defined as the point where two or more edges meet. The rays begin and go in two different directions from the vertex.

In geometry we can say that, it is where each angular point of a polygon, polyhedron, or other figure.

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I know this is a supervised data mining task because (choose all that apply) A. Because the target belonged to the same group as

Vinvika [58]

Answer:

The answer to your question is C. There a specific quantifiable target that we are interested in or trying to predict.

Step-by-step explanation:

I hope this helps and have a good day!

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3 years ago

Amy has 12 pairs of white socks, 2 pairs of gray socks, and 6 pairs of black socks in her drawer. if she takes two pairs without

KIM [24]

HI!
First of all, there are total 12 + 2 + 6 = 20 pairs of socks.
Probability of getting a pair of white socks the first time is 12/20.
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Therefore the probability that she will take a white pair and gray pair without replacement is 6/95 (I multiplied the two probabilities)
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4 years ago

Robert earned $10, which was 4 less than twice what Eric earned. How much money did Eric earn?

alexira [117]

Answer:

either 14 or 18

Step-by-step explanation:

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3 years ago

Rich is building a travel crate for his dog, Thomas, a beagle mix who is about 30 inches tall. For Thomas to travel safely, his

sukhopar [10]

2160 inches is the answer I think but not quite sure

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3 years ago

Read 2 more answers

The time it takes for a planet to complete its orbit around a particular star is called the? planet's sidereal year. The siderea

BartSMP [9]

Answer:

(a) See below

(b) r = 0.9879

(d) See below

(e) No.

Step-by-step explanation:

(a) Plot the data

I used Excel to plot your data and got the graph in Fig 1 below.

(b) Correlation coefficient

One formula for the correlation coefficient is

$r = \dfrac{\sum{xy} - \sum{x} \sum{y}}{\sqrt{\left [n\sum{x}^{2}-\left (\sum{x}\right )^{2}\right]\left [n\sum{y}^{2} -\left (\sum{y}\right )^{2}\right]}}$

The calculation is not difficult, but it is tedious.

(i) Calculate the intermediate numbers

We can display them in a table.

x y xy x² y²

36 0.22 7.92 1296 0.05

67 0.62 42.21 4489 0.40

93 1.00 93.00 20164 3.46

433 11.8 5699.4 233289 139.24

887 29.3 25989.1 786769 858.49

1785 82.0 146370 3186225 6724

2797 163.0 455911 7823209 26569

3675 248.0 911400 13505625 61504

9965 537.81 1545776.75 25569715 95799.63

(ii) Calculate the correlation coefficient

$r = \dfrac{\sum{xy} - \sum{x} \sum{y}}{\sqrt{\left [n\sum{x}^{2}-\left (\sum{x}\right )^{2}\right]\left [n\sum{y}^{2} -\left (\sum{y}\right )^{2}\right]}}\\\\= \dfrac{9\times 1545776.75 - 9965\times 537.81}{\sqrt{[9\times 25569715 -9965^{2}][9\times 95799.63 - 537.81^{2}]}} \approx \mathbf{0.9879}$

(c) Regression line

The equation for the regression line is

y = a + bx where

$a = \dfrac{\sum y \sum x^{2} - \sum x \sum xy}{n\sum x^{2}- \left (\sum x\right )^{2}}\\\\= \dfrac{537.81\times 25569715 - 9965 \times 1545776.75}{9\times 25569715 - 9965^{2}} \approx \mathbf{-12.629}\\\\b = \dfrac{n \sum xy - \sum x \sum y}{n\sum x^{2}- \left (\sum x\right )^{2}} - \dfrac{9\times 1545776.75 - 9965 \times 537.81}{9\times 25569715 - 9965^{2}} \approx\mathbf{0.0654}\\\\\\\text{The equation for the regression line is $\large \boxed{\mathbf{y = -12.629 + 0.0654x}}$}$

(d) Residuals

Insert the values of x into the regression equation to get the estimated values of y.

Then take the difference between the actual and estimated values to get the residuals.

x y Estimated Residual

36 0.22 -10 10

67 0.62 -8 9

93 1.00 -7 8

142 1.86 -3 5

433 11.8 19 - 7

887 29.3 45 -16

1785 82.0 104 -22

2797 163.0 170 - 7

3675 248.0 228 20

(e) Suitability of regression line

A linear model would have the residuals scattered randomly above and below a horizontal line.

Instead, they appear to lie along a parabola (Fig. 2).

This suggests that linear regression is not a good model for the data.

4 0

3 years ago