Matrices and Determinants is a very important topic in Mathematics. Although it is taught to students from 12th to Graduation Level, in this article we’ll provide you step by step lessons, MCQs and Numerical of **IIT JAM Level** (M.Sc.). Get **Eduncle’s study notes** with formulas, questions and solutions to know what are Matrix and Determinant and how to solve these questions.

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In this brain-friendly guide, you’ll study and quickly grasp following concepts:

**1. Introduction – What are Matrix and Determinants?**

**2. Matrix and Determinant (All Formulas)**

**3. Theory**

**4.1 Basic Level Questions (3 Questions)**

**4.2 Challenging Questions (3 Questions)**

**4.3 Question asked in IIT JAM from Matrix and Determinant (5 Questions)**

**5. Related topics to be studied before readingÂ Matrix and Determinant.**

So, load your brain with these important concepts! After completing all the topics, try solving the following questions and you will easily score full marks from this unit. Answers to these questions are given in the end. You can verify your answers and check your level of understanding.

**What Are Matrix and Determinants? – Introduction**

The knowledge of matrices and determinants applies to several branches of science, as well as different mathematical discipline. Matrices are one of the most powerful tools in mathematics. It simplifies our work to a great extent when compared with other direct methods. The transformation of concept of matrices results in obtaining compact and simple methods of solving system of linear equations.

**Applications:**

We use Matrices not only for the representation of the coefficients in system of linear equations, but itâ€™s uses far exceeds.

The notation and operations of Matrices are used in electronic spreadsheet programs for personal computer, which can be further used in different areas of business and science like budgeting, sales projection, cost estimation, analyzing the results of an experiment etc.

Also, many physical operations such as magnification, rotation and reflection through a plane can be represented mathematically by matrices.

Matrices are also used in cryptography.

This mathematical tool is not only used in certain branches of sciences, but also in genetics, economics, sociology, modern psychology and industrial management.

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**Matrix and Determinants (All Formulas)**

Any matrix A and its transpose both have the same Eigen values.

The trace of the matrix equals to the sum of the Eigen values of a matrix.

The determinant of the matrix A equals to the product of the Eigen values of A.

If Î»

_{1}, Î»

_{2}, ….., Î»

_{n}Â are the n-Eigen values of A, then

Cayley Hamilton Theorem

A be an nxn matrix and let

**Matrix exponential**for a square matrix A,

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**Description**

A matrix (plural matrices) is an ordered rectangular table of elements (or entries). The numbers or functions are called the elements or the entries of the matrix.

We denote matrices by capital letters.

For example:

In the above examples, the horizontal lines of elements are called rows of the matrix and the vertical lines of elements are called columns of the matrix. Thus A has 3 rows and 2 columns, B has 3 rows and 3 columns while C has 2 rows and 3 columns.

**Order of a matrix**

A matrix having m rows and n columns is called a matrix of order m Ã— n or simply m Ã— n matrix (read as an m by n matrix). So referring to the above examples of matrices, we have A as 3 Ã— 2 matrix, B as 3 Ã— 3 matrix and C as 2 Ã— 3 matrix. We observe that A has 3 Ã— 2 = 6 elements, B and C have 9 and 6 elements, respectively.

In general, an m Ã— n matrix has the following rectangular array:

orÂ Â Â Â Â Â Â Â A = [aij]_{mÃ—n}, 1 â‰¤ i â‰¤ m, 1 â‰¤ j â‰¤ n i, j âˆˆ N

Thus the ithÂ row consists of the elements a_{i1}, a_{i2}, a_{i3}, …, a_{in}, while the jthÂ column consists of the elements a_{1j}, a_{2j}, a_{3j}, …, a_{mj},

In general a_{ij}, is an element lying in the i^{th}Â row and j^{th}Â column. We can also read it as the (i, j)^{th}Â element of A. The number of elements in an m Ã— n matrix will be equal to mn.

**Determinant**

To every square matrix A = [a_{ij}] of order n, we can associate a number (real or complex) called determinant of the matrix A, written as det A, where a_{ij}Â is the (i, j)^{th}Â element of A.

**NOTE:**

(i)Â Â Â Â Â Â Â Â Only square matrices have determinants.

(ii)Â Â Â Â Â Â Â For a matrix A, |A| is called determinant of A and not modulus of A.

**Determinant of a Matrix of Order One**

Let A = [a] be the matrix of order 1, then determinant of A is defined to be equal to a.

**Determinant of a Matrix of Order Two**

**Determinant of a Matrix of Order Three**

The determinant of a matrix of order three can be determined by expressing it in terms of second order determinants which is known as expansion of determinant along a row (or a column). There are six way of expanding a determinant of order 3 corresponding to each of three rows (R_{1}, R_{2}Â and R_{3}) and three columns (C_{1}, C_{2}Â and C_{3}) and each way gives the same value.

Consider the determinant of a square matrix A = [a_{ij}]_{3Ã—3}, i.e.

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**Eigen values and Eigen vectors**

**Definitions:**

**Â Â Â Â Â Â Â Â Â Â Â **Let A = [a_{ij}]_{nÃ—n}Â be a square matrix of order n, I is an unit matrix of order n and Î» an indeterminate, then the matrix.

Also the equation |A â€“ Î»| = 0, is called the **characteristic equation **of A. The roots of this equations are called the **characteristic roots or characteristic value or Eigen roots or Eigen values of latent roots** of the matrix.

The set of the Eigen values of the matrix A is called the **spectrum** of the matrix A. If Î» is a characteristic root of a n Ã— n matrix A, then the non-zero solution

of the equation A X = Î» X i.e. (A â€“ Î»|) X = 0 is called the characteristic vector or Eigen vector of the matrix A corresponding to the characteristic root Î».

**Chief Characteristics of Eigen Values**:

The sum of the elements of the principal diagonal of a matrix is called the trace of the matrix.

(i)Â Â Â Â Â Â Â Â Any matrix A and its transpose both have the same Eigen values.

(ii)Â Â Â Â Â Â Â The trace of the matrix equals to the sum of the Eigen values of a matrix.

(iii)Â Â Â Â Â Â The determinant of the matrix A equals to the product of the Eigen values of A.

(iv)Â Â Â Â Â Â If Î»_{1}, Î»_{2}, ….., Î»_{n}Â are the n-Eigen values of A, then

**Some important Theorems**

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**Cayley Hamilton Theorem**

**Practice Questions for Matrix and Determinants**

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**Basic Level Questions on Matrix and Determinant**

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**Multiple Selection Question**

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**Numerical Type Question**

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**Challenging Questions on Matrix and Determinant**

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**Multiple Selection Question**

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**Previous Year Questions on Matrix and Determinant**

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**Related Topics:**

Matrix and operations

Inverse of Matrix

Trace of a Matrix

Determinant

Minimal Polynomial

Type of Matrices

Algebraic and geometric multiplicity.

**FAQ:**

**What is the difference between matrix and determinants?**

**Key Difference:** A matrix or matrices is a rectangular grid of numbers or symbols that is represented in a row and column format. A determinant is a component of a square matrix and it cannot be found in any other type of matrix.

**Who invented matrix and determinants?**

**Â **

**Carl Gauss** (1777-1855), the greatest German **mathematician** of the 19th century, first used the term ‘determinant’ in 1801. Matrices began in the 2nd century BC with the Chinese although traces could be seen back in the 4th century BC with the Babylonians. Â It was only towards the end of the 17th century that much progress was made on the studies of matrices. Read more here â€“ **Matrix Mathematics**