Answer:
a) ∝A ∈ W
so by subspace, W is subspace of 3 × 3 matrix
b) therefore Basis of W is
={ ![{\left[\begin{array}{ccc}0&1&0\\-1&0&0\\0&0&0\end{array}\right]](https://tex.z-dn.net/?f=%7B%5Cleft%5B%5Cbegin%7Barray%7D%7Bccc%7D0%261%260%5C%5C-1%260%260%5C%5C0%260%260%5Cend%7Barray%7D%5Cright%5D)
![,\left[\begin{array}{ccc}0&0&1\\0&0&0\\-1&0&0\end{array}\right]](https://tex.z-dn.net/?f=%2C%5Cleft%5B%5Cbegin%7Barray%7D%7Bccc%7D0%260%261%5C%5C0%260%260%5C%5C-1%260%260%5Cend%7Barray%7D%5Cright%5D)
![,\left[\begin{array}{ccc}0&0&0\\0&0&1\\0&-1&0\end{array}\right]](https://tex.z-dn.net/?f=%2C%5Cleft%5B%5Cbegin%7Barray%7D%7Bccc%7D0%260%260%5C%5C0%260%261%5C%5C0%26-1%260%5Cend%7Barray%7D%5Cright%5D)
}
Step-by-step explanation:
Given the data in the question;
W = { A| Air Skew symmetric matrix}
= {A | A = -A^T }
A ; O⁻ = -O⁻^T O⁻ : Zero mstrix
O⁻ ∈ W
now let A, B ∈ W
A = -A^T B = -B^T
(A+B)^T = A^T + B^T
= -A - B
- ( A + B )
⇒ A + B = -( A + B)^T
∴ A + B ∈ W.
∝ ∈ | R
(∝.A)^T = ∝A^T
= ∝( -A)
= -( ∝A)
(∝A) = -( ∝A)^T
∴ ∝A ∈ W
so by subspace, W is subspace of 3 × 3 matrix
A ∈ W
A = -AT
A = ![\left[\begin{array}{ccc}o&a&b\\-a&o&c\\-b&-c&0\end{array}\right]](https://tex.z-dn.net/?f=%5Cleft%5B%5Cbegin%7Barray%7D%7Bccc%7Do%26a%26b%5C%5C-a%26o%26c%5C%5C-b%26-c%260%5Cend%7Barray%7D%5Cright%5D)
= ![a\left[\begin{array}{ccc}0&1&0\\-1&0&0\\0&0&0\end{array}\right]](https://tex.z-dn.net/?f=a%5Cleft%5B%5Cbegin%7Barray%7D%7Bccc%7D0%261%260%5C%5C-1%260%260%5C%5C0%260%260%5Cend%7Barray%7D%5Cright%5D)
![+b\left[\begin{array}{ccc}0&0&1\\0&0&0\\-1&0&0\end{array}\right]](https://tex.z-dn.net/?f=%2Bb%5Cleft%5B%5Cbegin%7Barray%7D%7Bccc%7D0%260%261%5C%5C0%260%260%5C%5C-1%260%260%5Cend%7Barray%7D%5Cright%5D)
![+c\left[\begin{array}{ccc}0&0&0\\0&0&1\\0&-1&0\end{array}\right]](https://tex.z-dn.net/?f=%2Bc%5Cleft%5B%5Cbegin%7Barray%7D%7Bccc%7D0%260%260%5C%5C0%260%261%5C%5C0%26-1%260%5Cend%7Barray%7D%5Cright%5D)
therefore Basis of W is
={ }
Yes
No
Yes
No
This is because in order to be addition property of equality they have to add/ subtract by the same exact amount on both sides.
Answer:
1.6%
Step-by-step explanation:
The cumulative distribution function (CDF) of a random variable X is denoted by F(x), and is defined as
F(x) = P(X ≤ x). where x is the largest possible value of X that is less than or equal to x
z = (x-μ)/σ,
where:
x is the raw score = 205
μ is the population mean, = 220 pounds
σ is the population standard deviation = 7 pounds
205 -220/7
z = -15/7
z = -2.1428571429
Using the normal cdf function on your graphing calculator,the cumulative distribution is
normalcdf( -2.1428571429, 100)
= 0.01606229
In percent form = 0.01606229 × 100
= 1.6%
Answer:
3xc8cx-(456c)+s5=23c
Step-by-step explanation:
