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Bad White [126]
3 years ago
7

Am I correct? Why am I wrong?

Mathematics
1 answer:
Ivenika [448]3 years ago
5 0

Answer:

u are correct

Step-by-step explanation:

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A ship leaves port at 1:00 P.M. and travels S35°E at the rate of 27 mi/hr. Another ship leaves the same port at 1:30 P.M. and tr
Len [333]

To solve this problem you must apply the proccedure shown below:

1. You must apply the Law of Cosines, as you can see in the figure attached. Then:

- The first ship travels at 27 mi/hr in for two hours. Therefore, the side a is:

a=(27 mi/hr)(2 hr)=54mi

- The second ship travels at 18 mi/hr for 1.5 hours. Therefore, the side b is:

b=(18mi/hr)(1.5hr)=27mi

- Now, you can calculate c:

c=\sqrt{54^{2}+27^{2}-2(54)(27)Cos(55)}=44 mi

The answer is: 44 miles

8 0
3 years ago
What is the solution to the following system of equations?
kipiarov [429]

Answer:

(0, -6)

Step-by-step explanation:

Given the following systems of linear equations;

3x - 2y = 12 ...... equation 1

16x - 4y = 24 ........ equation 2

We would solve for the solution using the elimination method;

Multiplying eqn 1 by 2, we have;

2 * (3x - 2y = 12)

6x - 4y = 24

16x - 4y = 24

Subtracting the two equations, we have;

(6x - 16x) + (-4y -[-4y]) = (24 - 24)

-10x - 0 = 0

-10x = 0

x = -0/10 = 0

Next, we would find the value of y;

3x - 2y = 12

3(0) - 2y = 12

0 - 2y = 12

-2y = 12

y = -12/2

y = -6

Check:

3x - 2y = 12

3(0) - 2(-6) = 12

0 - (-12) = 12

12 = 12

Note: the options provided for this questions are incorrect or inappropriate.

5 0
3 years ago
What do you know to be true about the values of a and b?
gizmo_the_mogwai [7]

Answer:

Can't be determined

Step-by-step explanation:

You just don't have enough info!

6 0
3 years ago
tensor-on-tensor regression: riemannian optimization, over-parameterization, statistical-computational gap and their interplay
Contact [7]

The purpose of the tensor-on-tensor regression, which we examine, is to relate tensor responses to tensor covariates with a low Tucker rank parameter tensor/matrix without being aware of its intrinsic rank beforehand.

By examining the impact of rank over-parameterization, we suggest the Riemannian Gradient Descent (RGD) and Riemannian Gauss-Newton (RGN) methods to address the problem of unknown rank. By demonstrating that RGD and RGN, respectively, converge linearly and quadratically to a statistically optimal estimate in both rank correctly-parameterized and over-parameterized scenarios, we offer the first convergence guarantee for the generic tensor-on-tensor regression. According to our theory, Riemannian optimization techniques automatically adjust to over-parameterization without requiring implementation changes.

Learn more about tensor-on-tensor here

brainly.com/question/16382372

#SPJ4

7 0
2 years ago
Look at the figure. Classify the pair of angles: <2 and <7.
s344n2d4d5 [400]

Answer:

Same-side exterior angles

Step-by-step explanation:

Through the process of elimination it is not:

→ Corresponding angles as that would be 2 and 6

→ Same side interior angles as that would be 3 and 6 or 4 and 5

→ Alternate interior angles as that would be 6 and 4 of 3 and 5

3 0
3 years ago
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