Easy Multivariate Analysis MCQs – 1

Multivariate Analysis term includes all statistics for more than two simultaneously analyzed variables. The post contains Multivariate Analysis MCQs. Let us start with the Online Multivariate Analysis MCQs test.

Multivariate Analysis MCQs

• If $A$ and $B$ are two $n \times n$ matrices, which of the following is not always true?
• Let $x_1, x_2, \cdots, x_n$ be a random sample from a joint distribution with mean vector $\mu$ and covariance $\sigma$. Then $\overline{x}$ is an unbiased estimator of $\mu$ and its covariance matrix is:
• Let $x$ be distributed as $N_p(\mu, \sigma)$ with $|\sigma | > 0$, then $(x-\mu)’ \sigma^{-1} (x-\mu)$ is distributed as:
• Let $A$ be a $k\times k$ symmetric matrix and $X$ be a $k\times 1$ vector. Then
• Let $x_1, x_2, \cdots, x_n$ be a random sample of size $n$ from a p-variate normal distribution with mean $\mu$ and covariance matrix $\sigma$, then
• The set of all linear combination of $X_1, X_2, \cdots, X_k$ is called
• A set of vectors $X_1, X_2, \cdots, X_n$ are linearly independent if
• Length of vector $\underline{X}$ is calculated as
• A matrix in which the number of rows and columns are equal is called
• A matrix $A_{m\times n}$ is defined to be orthogonal if
• If $A$ is a square matrix of order ($m \times m$) then the sum of diagonal elements is called
• The rank of a matrix $\begin{bmatrix}1 & 0 & 1 & 0 & 2 \ 0 & 0 & 1 & 1 & 2 \ 1 & 1 & 0 & 0 & 2 \ 0 & 1 & 1 & 1 & 3\end{bmatrix}$ is
• If $A$ is a square matrix, then $det(A – \lambda)=0$ is known as
• The pdf of multivariate normal distribution exists only when $\sigma$ is
• The eigenvalue is the factor by which the Eigenvector is
• Eigenvalue is often introduced in the context of
• How many Eigenvalues does a 2 by 2 matrix have?
• What are Eigenvalues?
• Eigenvalues and Eigenvectors are only for the matrices
• A square matrix $A$ and its transpose have the Eigenvalues

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