Answer:
c = 13.52 units.
Step-by-step explanation:
So for this, lets use the Law of Sines, which says that:
Sin A / a = Sin B / b = Sin C / c
We have everything for this except the the angle measure of angle C. This can be found by doing 180 - 80 - 33, since the total interior angle measure of a triangle always equals 180 degrees.
180 - 80 - 33 = 67 degrees
With this, we can use the angle & side of A/a as well as the angle of C to get the side of c by using the Law of Sines
Sin A / a = Sin C / c
sin 33/8 = sin 67/c
c = 8*sin67 / sin 33
c = 13.52 units.
Answer:
All you have to do is to the distributive method.
Step-by-step explanation:
(7x+14)(9x-8)
Answer:
It's 2
Step-by-step explanation:
X is 2 because if you multiply two by two you get 4
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
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Answer:
262.6/300% for the first 3 test if you were to add another test it would be 400% total and you need 360% of test grades to have an average of 90% and so 360 - 262.6 = 97.4%
Step-by-step explanation:
