Data Structure MCQ - Matrix
Q1.What is the order of a matrix?
- number of rows X number of columns
- number of columns X number of rows
- number of rows X number of rows
- number of columns X number of columns
Answer:- (A).
Explanations :By definition, the order of a matrix is number of rows X number of columns, generally denoted by mXn(not compulsory).
Explanations :By definition, the order of a matrix is number of rows X number of columns, generally denoted by mXn(not compulsory).
- Associative
- Distributive
- Commutative
- None of these
Answer:- (C).
- int *arr = malloc(r * c * sizeof(int));
- int *arr = (int *)malloc(r * c * sizeof(int));
- int *arr = (int *)malloc(r + c * sizeof(int));
- int *arr = (int *)malloc(r * c * sizeof(arr));
Answer:- (B).
Explanations :int *arr = (int *)malloc(r * c * sizeof(int));
Total number of elements in the matrix will be r*c
Explanations :int *arr = (int *)malloc(r * c * sizeof(int));
Total number of elements in the matrix will be r*c
for(int i = 0; i < row; i++) { for(int j = 0; j < column; j++) { if(i == j) sum = sum + (array[i][j]); } } System.out.println(sum);
- Normal of a matrix
- Trace of a matrix
- Square of a matrix
- Transpose of a matrix
Answer:- (B).
Explanations :trace of a matrix is the sum of the principal diagonal elements.
Explanations :trace of a matrix is the sum of the principal diagonal elements.
- In solving linear equations
- Image processing
- Graph theory
- All of these
Answer:- (D).
Explanations :Solving linear equations is a separate field in Mathematics involving matrices, Image processing stores the pixels in the form of matrices, and the graphs are represented with the help of matrices to indicate the nodes and edges.
Explanations :Solving linear equations is a separate field in Mathematics involving matrices, Image processing stores the pixels in the form of matrices, and the graphs are represented with the help of matrices to indicate the nodes and edges.
- Internal complexity
- Searching through a matrix is complex
- Not space efficient
- All of these
Answer:- (D).
Explanations :time complexity of a matrix is O(n2) and sometimes the internal organization becomes tedious.
Explanations :time complexity of a matrix is O(n2) and sometimes the internal organization becomes tedious.
- Identity matrix
- Inverse of A
- Square of A
- Transpose of A
Answer:- (B).
Explanations :Any square matrix when multiplied with its inverse gives the identity matrix. Note that non square matrices are not invertible.
Explanations :Any square matrix when multiplied with its inverse gives the identity matrix. Note that non square matrices are not invertible.
- Identity Matrix
- Unit Matrix
- Sparse Matrix
- Zero Matrix
Answer:- (C).
Explanations :Sparse Matrix is a matrix in which most of the elements are Zero. Identity Matrix is a matrix in which all principle diagonal elements are 1 and rest of the elements are Zero. Unit Matrix is also called Identity Matrix. Zero Matrix is a matrix in which all the elements are Zer
Explanations :Sparse Matrix is a matrix in which most of the elements are Zero. Identity Matrix is a matrix in which all principle diagonal elements are 1 and rest of the elements are Zero. Unit Matrix is also called Identity Matrix. Zero Matrix is a matrix in which all the elements are Zer
- Harry Markowitz
- James Sylvester
- Chris Messina
- Arthur Cayley
Answer:- (A).
Explanations :Harry Markowitz coined the term Sparse Matrix. James Sylvester coined the term Matrix. Chris Messina coined the term Hashtag and Arthur Cayley developed the algebraic aspects of a matrix.
Explanations :Harry Markowitz coined the term Sparse Matrix. James Sylvester coined the term Matrix. Chris Messina coined the term Hashtag and Arthur Cayley developed the algebraic aspects of a matrix.
- Dictionary of Keys
- Linked List
- Array
- Heap
Answer:- (D).
Explanations :Heap is not used to represent Sparse Matrix while in Dictionary, rows and column numbers are used as Keys and values as Matrix entries, Linked List is used with each node of Four fields (Row, Column, Value, Next Node) (2D array is used to represent the Sparse Matrix with three fields (Row, Column, Value).
Explanations :Heap is not used to represent Sparse Matrix while in Dictionary, rows and column numbers are used as Keys and values as Matrix entries, Linked List is used with each node of Four fields (Row, Column, Value, Next Node) (2D array is used to represent the Sparse Matrix with three fields (Row, Column, Value).
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