Answer:
is that a cat
Step-by-step explanation:
The eigenvectors are (1 + i)/4 and (1-i)/4.
- A matrix is an organized, rectangular grouping of real or complex integers or functions.
- The unique collection of scalars known as eigenvalues is connected to the system of linear equations. The majority of matrix equations employ it. The German term "Eigen" signifies "appropriate" or "characteristic." Therefore, the word "eigenvalue" can also be used to refer to a suitable value, a latent root, a characteristic value, or a characteristic root. The eigenvalue is a scalar that is used to alter the eigenvector, to put it simply.
- The non-zero vectors that do not change direction when a linear transformation is performed are called eigenvectors. It is only modified by a single scalar component.
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Not always. It depends on the teacher and the school. Depends on the rules and how your being tought.
Yep it’s B or 20 outcomes
Answer:
D
Step-by-step explanation:
The mean of a standard normal distribution is always = 0 with the standard deviation being equal to. Therefore a standard normal distribution is a normal distribution described with a mean of 0 and standard deviation of 1. Since a standard normal distribution is centered at the middle with equal distribution to both the left and right of the distribution. The centre point is 0, which is the mean and the standard deviation is 1 to either side of the distribution.