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Elden [556K]
3 years ago
11

Plz halp. I just need #20, and please write out the equation so I know how to do it for future problems, thanks!

Mathematics
1 answer:
FrozenT [24]3 years ago
6 0
The number you need is 16 all you have to do is work out the problem and try to understand it they are trying to confuse you don't need an equation.
Hope this help!
Have a Great day mate !!
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I need help in less than 20 mins what is 19 times 36000 divided by 8 times 2?whoever help sub to this clipz_content on yt and ge
Aleksandr [31]

Answer:

I pretty sure the answer is 171,000 . but if i'm wrong someone can correct me

Step-by-step explanation:

4 0
2 years ago
What is the value of the expression below if y=5
ale4655 [162]

Answer:

27

Step-by-step explanation:

Its a long step by step but trust me

6 0
2 years ago
Chitra has 8 4/5 room
ycow [4]

Answer:

She can paint 4 rooms.

Step-by-step explanation:

8\dfrac{4}{5} \div 2\dfrac{1}{5}=\dfrac{(8\times 5+4) \times 5}{5 \times (2\times 5 + 1)}=\dfrac{44}{11}=4

8 0
3 years ago
Which radian measure is equivalent to −15°? −9π/20 −12/π −20π/9 −π/12
Reika [66]

Answer:

<h3>-π/12</h3>

Step-by-step explanation:

Which radian measure is equivalent to −15°? −9π/20 −12/π −20π/9 −π/12

180 degrees = πrad

-15 degrees = x

Cross multiply

180x = -15π

x = -15π/180

x = -π/12

Hence the value of -15 degrees in radians is -π/12

3 0
2 years ago
on the asymptotic behavior of the sample estimates of eigenvalues and eigenvectors of covariance matrices
skelet666 [1.2K]

A complex mathematical topic, the asymptotic behavior of sequences of random variables, or the behavior of indefinitely long sequences of random variables, has significant ramifications for the statistical analysis of data from large samples.

The asymptotic behavior of the sample estimators of the eigenvalues and eigenvectors of covariance matrices is examined in this claim. This work focuses on limited sample size scenarios where the number of accessible observations is comparable in magnitude to the observation dimension rather than usual high sample-size asymptotic .

Under the presumption that both the sample size and the observation dimension go to infinity while their quotient converges to a positive value, the asymptotic behavior of the conventional sample estimates is examined using methods from random matrix theory.

Closed form asymptotic expressions of these estimators are obtained, demonstrating the inconsistency of the conventional sample estimators in these asymptotic conditions, assuming that an asymptotic eigenvalue splitting condition is satisfied.

To learn more about asymptotic behavior visit:brainly.com/question/17767511

#SPJ4

4 0
1 year ago
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