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Summary

Summary of Chapter 3: Matrices

Matrices are fundamental tools in mathematics, offering a compact and simplified method for solving systems of linear equations. Beyond their mathematical applications, matrices are utilized in various fields such as business, science, cryptography, genetics, economics, sociology, psychology, and industrial management. They are instrumental in operations like magnification, rotation, and reflection, and are used in electronic spreadsheets for tasks like budgeting and sales projection. This chapter introduces the fundamentals of matrix and matrix algebra, exploring their diverse applications and operations.

Learning Objectives

  • Understand the concept and definition of matrices.
  • Identify the various types of matrices, including symmetric and skew symmetric matrices.
  • Perform matrix operations such as addition, subtraction, and multiplication.
  • Apply the properties of matrix operations, including commutative, associative, and distributive laws.
  • Use matrices to solve systems of linear equations.
  • Explore the applications of matrices in different fields such as business, science, and cryptography.
  • Verify matrix identities using examples, such as (AB)=BA(AB)' = B'A'.
  • Calculate the inverse of a matrix and understand its uniqueness.
  • Express any square matrix as the sum of a symmetric and a skew symmetric matrix.
  • Prove properties of matrices using mathematical induction and other methods.

Detailed Notes

Matrices

Introduction

  • Matrices are essential in various branches of mathematics.
  • They simplify solving systems of linear equations and are used in electronic spreadsheets for business and science applications.
  • Matrices represent physical operations like magnification, rotation, and reflection, and are used in cryptography, genetics, economics, sociology, psychology, and industrial management.

Matrix Basics

  • A matrix is an ordered rectangular array of numbers or functions.
  • A matrix with mm rows and nn columns is of order m×nm \times n.
  • Types of matrices:
    • Column Matrix: [aij]m×1[a_{ij}]_{m \times 1}
    • Row Matrix: [aij]1×n[a_{ij}]_{1 \times n}
    • Square Matrix: When m=nm = n.
    • Diagonal Matrix: aij=0a_{ij} = 0 when iji \neq j.
    • Scalar Matrix: aij=0a_{ij} = 0 when iji \neq j, aij=ka_{ij} = k when i=ji = j.
    • Identity Matrix: aij=1a_{ij} = 1 when i=ji = j, aij=0a_{ij} = 0 when iji \neq j.
    • Zero Matrix: All elements are zero.

Matrix Operations

  • Addition: A+B=B+AA + B = B + A
  • Multiplication: If A=[aij]m×nA = [a_{ij}]_{m \times n} and B=[bjk]n×pB = [b_{jk}]_{n \times p}, then AB=C=[cik]m×pAB = C = [c_{ik}]_{m \times p}.
  • Transpose: A=[aji]n×mA' = [a_{ji}]_{n \times m}
    • Properties:
      • (A)=A(A')' = A
      • (kA)=kA(kA)' = kA'
      • (A+B)=A+B(A + B)' = A' + B'
      • (AB)=BA(AB)' = B'A'

Special Matrices

  • Symmetric Matrix: A=AA' = A
  • Skew Symmetric Matrix: A=AA' = -A
  • Any square matrix can be represented as the sum of a symmetric and a skew symmetric matrix.

Invertible Matrices

  • A square matrix AA is invertible if there exists a matrix BB such that AB=BA=IAB = BA = I.
  • The inverse of a matrix, if it exists, is unique.
  • If AA and BB are invertible, then (AB)1=B1A1(AB)^{-1} = B^{-1}A^{-1}.

Examples

  • Example 1: If A=[2314]A = \begin{bmatrix} 2 & 3 \\ 1 & 4 \end{bmatrix}, find AA', A1A^{-1}, and verify AA1=IAA^{-1} = I.
  • Example 2: Given matrices AA and BB, show (A+B)=A+B(A + B)' = A' + B'.

Applications

  • Used in solving linear equations, business applications, physical transformations, and various scientific fields.

Exercises

  • Prove properties of transpose and inverse matrices.
  • Solve matrix equations and verify results using matrix operations.

Exam Tips & Common Mistakes

Common Mistakes and Exam Tips

  • Matrix Multiplication Order: Remember that matrix multiplication is not commutative, i.e., ABBAAB \neq BA. Always pay attention to the order of multiplication.
  • Inverse of a Matrix: A rectangular matrix does not possess an inverse. Only square matrices can have inverses, and the inverse is unique if it exists.
  • Symmetric and Skew Symmetric Matrices: For any square matrix AA, A+AA + A' is symmetric, and AAA - A' is skew symmetric. Ensure you understand these properties to avoid confusion in problems.
  • Transpose Properties: The transpose of a product of matrices (AB)=BA(AB)' = B'A'. This property is crucial in simplifying expressions involving transposes.
  • Matrix Equations: When solving matrix equations, ensure the dimensions are compatible for operations like addition, subtraction, and multiplication.
  • Verification of Properties: Always verify properties such as (A+B)=A+B(A + B)' = A' + B' and (kA)=kA(kA)' = kA' with examples to solidify understanding.
  • Zero and Identity Matrices: Be cautious with zero and identity matrices in operations as they have unique properties that can simplify or complicate problems if not handled correctly.
  • Checking for Invertibility: A matrix is invertible if AB=BA=IAB = BA = I. Ensure to verify this condition when asked about invertibility.
  • Use of Induction: For proving results involving matrices, such as powers of matrices, mathematical induction can be a powerful tool. Ensure you are comfortable with this method.
  • Exam Practice: Practice problems involving matrix operations, properties, and proofs as they are common in exams and can often be tricky if not well understood.

Practice & Assessment

Multiple Choice Questions

A.

[1001]\begin{bmatrix} 1 & 0 \\ 0 & 1 \end{bmatrix}

B.

[0110]\begin{bmatrix} 0 & 1 \\ 1 & 0 \end{bmatrix}

C.

[1001]\begin{bmatrix} -1 & 0 \\ 0 & -1 \end{bmatrix}

D.

[0110]\begin{bmatrix} 0 & -1 \\ -1 & 0 \end{bmatrix}
Correct Answer: A

Solution:

The inverse of the identity matrix II is itself, II. Therefore, the inverse of AA is [1001]\begin{bmatrix} 1 & 0 \\ 0 & 1 \end{bmatrix}.

A.

0

B.

3

C.

9

D.

6
Correct Answer: C

Solution:

The determinant of a 2x2 matrix [abcd]\begin{bmatrix} a & b \\ c & d \end{bmatrix} is calculated as adbcad - bc. For matrix A, the determinant is 3×30×0=93 \times 3 - 0 \times 0 = 9.

A.

A

B.

I - A

C.

I

D.

3A
Correct Answer: B

Solution:

If A2=AA^2 = A, then (I+A)37A=IA(I + A)^3 - 7A = I - A.

A.

3

B.

1

C.

4

D.

2
Correct Answer: A

Solution:

The eigenvalues of AA are found by solving det(AλI)=0\det(A - \lambda I) = 0. For A=[2112]A = \begin{bmatrix} 2 & 1 \\ 1 & 2 \end{bmatrix}, the eigenvalues are 33 and 11.

A.

₹10,000

B.

₹12,000

C.

₹15,000

D.

₹18,000
Correct Answer: D

Solution:

Let the amount invested in the first bond be ₹x. Then, the amount in the second bond is ₹(30,000 - x). The total interest is given by the equation: 0.05x+0.07(30,000x)=18000.05x + 0.07(30,000 - x) = 1800. Solving, 0.05x+21000.07x=18000.02x=300x=15,0000.05x + 2100 - 0.07x = 1800 \Rightarrow -0.02x = -300 \Rightarrow x = 15,000. Therefore, the amount invested in the first bond is ₹15,000.

A.

1

B.

-1

C.

-2

D.

3
Correct Answer: C

Solution:

The determinant of AA is calculated as (2×5)(3×4)=1012=2(2 \times 5) - (3 \times 4) = 10 - 12 = -2.

A.

1 TT : 2 Tt : 1 tt

B.

3 TT : 1 tt

C.

1 Tt : 2 TT : 1 tt

D.

2 TT : 1 Tt : 1 tt
Correct Answer: A

Solution:

The genotypic ratio for a monohybrid cross in the F2 generation is 1 homozygous dominant (TT) : 2 heterozygous (Tt) : 1 homozygous recessive (tt).

A.

[2143]\begin{bmatrix} 2 & 1 \\ 4 & 3 \end{bmatrix}

B.

[1001]\begin{bmatrix} 1 & 0 \\ 0 & 1 \end{bmatrix}

C.

[2002]\begin{bmatrix} 2 & 0 \\ 0 & 2 \end{bmatrix}

D.

[0110]\begin{bmatrix} 0 & 1 \\ 1 & 0 \end{bmatrix}
Correct Answer: A

Solution:

The product AB=[1×0+2×11×1+2×03×0+4×13×1+4×0]=[2143]AB = \begin{bmatrix} 1 \times 0 + 2 \times 1 & 1 \times 1 + 2 \times 0 \\ 3 \times 0 + 4 \times 1 & 3 \times 1 + 4 \times 0 \end{bmatrix} = \begin{bmatrix} 2 & 1 \\ 4 & 3 \end{bmatrix}.

A.

[3231]\begin{bmatrix} 3 & 2 \\ \sqrt{3} & -1 \end{bmatrix}

B.

[3312]\begin{bmatrix} 3 & \sqrt{3} \\ -1 & 2 \end{bmatrix}

C.

[3132]\begin{bmatrix} 3 & -1 \\ \sqrt{3} & 2 \end{bmatrix}

D.

[3321]\begin{bmatrix} 3 & \sqrt{3} \\ 2 & -1 \end{bmatrix}
Correct Answer: A

Solution:

The transpose of a matrix is obtained by swapping its rows and columns. Thus, the transpose of A=[3321]A = \begin{bmatrix} 3 & \sqrt{3} \\ 2 & -1 \end{bmatrix} is [3231]\begin{bmatrix} 3 & 2 \\ \sqrt{3} & -1 \end{bmatrix}.

A.

A

B.

B

C.

Both A and B

D.

Neither A nor B
Correct Answer: B

Solution:

The matrix B is symmetric, and for a symmetric matrix, the transpose is equal to the matrix itself. Therefore, if B is also its own inverse, then the transpose is equal to the inverse.

A.

₹3000

B.

₹3500

C.

₹4000

D.

₹4500
Correct Answer: A

Solution:

The total cost is calculated as follows: 1000×0.40+500×1.00+5000×0.50=400+500+2500=34001000 \times 0.40 + 500 \times 1.00 + 5000 \times 0.50 = 400 + 500 + 2500 = 3400 paise, which is ₹34.00. Therefore, the total cost incurred is ₹34.00.

A.

₹5,000

B.

₹10,000

C.

₹15,000

D.

₹20,000
Correct Answer: A

Solution:

Calculate the total revenue from sales and subtract the total cost. Revenue: ₹(2.50 \times 10,000 + 1.50 \times 10,000 + 1.00 \times 10,000) = ₹50,000. Cost: ₹(2.00 \times 10,000 + 1.00 \times 10,000 + 0.50 \times 10,000) = ₹45,000. Gross profit = ₹50,000 - ₹45,000 = ₹5,000.

A.

All eigenvalues are zero

B.

The eigenvalues are 0, 23, and 40

C.

The eigenvalues are 23 and 40

D.

The eigenvalues are the roots of the characteristic polynomial
Correct Answer: D

Solution:

The equation A323A40I=OA^3 - 23A - 40I = O implies that the eigenvalues of A satisfy the characteristic equation λ323λ40=0\lambda^3 - 23\lambda - 40 = 0.

A.

It is a symmetric matrix.

B.

It is a skew symmetric matrix.

C.

It is a diagonal matrix.

D.

It is an identity matrix.
Correct Answer: B

Solution:

If A and B are symmetric matrices, then AB - BA is a skew symmetric matrix.

A.

5

B.

6

C.

7

D.

8
Correct Answer: B

Solution:

The trace of a matrix is the sum of the elements on its main diagonal. For matrix A, the trace is 1+4=51 + 4 = 5.

A.

[211.50.5]\begin{bmatrix} -2 & 1 \\ 1.5 & -0.5 \end{bmatrix}

B.

[4231]\begin{bmatrix} 4 & -2 \\ -3 & 1 \end{bmatrix}

C.

[1001]\begin{bmatrix} 1 & 0 \\ 0 & 1 \end{bmatrix}

D.

Matrix A does not have an inverse.
Correct Answer: A

Solution:

The inverse of a 2x2 matrix [abcd]\begin{bmatrix} a & b \\ c & d \end{bmatrix} is 1adbc[dbca]\frac{1}{ad-bc}\begin{bmatrix} d & -b \\ -c & a \end{bmatrix}. For matrix A, the inverse is 11×42×3[4231]=[211.50.5]\frac{1}{1\times4 - 2\times3}\begin{bmatrix} 4 & -2 \\ -3 & 1 \end{bmatrix} = \begin{bmatrix} -2 & 1 \\ 1.5 & -0.5 \end{bmatrix}.

A.

0

B.

1

C.

2

D.

3
Correct Answer: B

Solution:

First, calculate A2=[2314][2314]=[718619]A^2 = \begin{bmatrix} 2 & 3 \\ 1 & 4 \end{bmatrix} \begin{bmatrix} 2 & 3 \\ 1 & 4 \end{bmatrix} = \begin{bmatrix} 7 & 18 \\ 6 & 19 \end{bmatrix}. Then, 2A=2×[2314]=[4628]2A = 2 \times \begin{bmatrix} 2 & 3 \\ 1 & 4 \end{bmatrix} = \begin{bmatrix} 4 & 6 \\ 2 & 8 \end{bmatrix}. Now, C=[718619][4628]+[1001]=[412412]C = \begin{bmatrix} 7 & 18 \\ 6 & 19 \end{bmatrix} - \begin{bmatrix} 4 & 6 \\ 2 & 8 \end{bmatrix} + \begin{bmatrix} 1 & 0 \\ 0 & 1 \end{bmatrix} = \begin{bmatrix} 4 & 12 \\ 4 & 12 \end{bmatrix}. The determinant of CC is 4×124×12=04 \times 12 - 4 \times 12 = 0.

A.

5

B.

6

C.

7

D.

8
Correct Answer: C

Solution:

The matrix AB=[2314][0110]=[2204]A - B = \begin{bmatrix} 2 & 3 \\ 1 & 4 \end{bmatrix} - \begin{bmatrix} 0 & 1 \\ 1 & 0 \end{bmatrix} = \begin{bmatrix} 2 & 2 \\ 0 & 4 \end{bmatrix}. The determinant is calculated as 2×42×0=82\times4 - 2\times0 = 8.

A.

[0000]\begin{bmatrix} 0 & 0 \\ 0 & 0 \end{bmatrix}

B.

[1001]\begin{bmatrix} 1 & 0 \\ 0 & 1 \end{bmatrix}

C.

[2314]\begin{bmatrix} -2 & -3 \\ -1 & -4 \end{bmatrix}

D.

[2314]\begin{bmatrix} 2 & 3 \\ 1 & 4 \end{bmatrix}
Correct Answer: A

Solution:

First, calculate A2=[2314][2314]=[718619]A^2 = \begin{bmatrix} 2 & 3 \\ 1 & 4 \end{bmatrix} \begin{bmatrix} 2 & 3 \\ 1 & 4 \end{bmatrix} = \begin{bmatrix} 7 & 18 \\ 6 & 19 \end{bmatrix}. Then, compute 5A=5[2314]=[1015520]5A = 5 \begin{bmatrix} 2 & 3 \\ 1 & 4 \end{bmatrix} = \begin{bmatrix} 10 & 15 \\ 5 & 20 \end{bmatrix} and 6B=6[1001]=[6006]6B = 6 \begin{bmatrix} 1 & 0 \\ 0 & 1 \end{bmatrix} = \begin{bmatrix} 6 & 0 \\ 0 & 6 \end{bmatrix}. Therefore, C=A25A+6B=[718619][1015520]+[6006]=[0000]C = A^2 - 5A + 6B = \begin{bmatrix} 7 & 18 \\ 6 & 19 \end{bmatrix} - \begin{bmatrix} 10 & 15 \\ 5 & 20 \end{bmatrix} + \begin{bmatrix} 6 & 0 \\ 0 & 6 \end{bmatrix} = \begin{bmatrix} 0 & 0 \\ 0 & 0 \end{bmatrix}.

A.

10

B.

12

C.

14

D.

16
Correct Answer: A

Solution:

The product AB=[1234][2012]=[1×2+2×11×0+2×23×2+4×13×0+4×2]=[44108]AB = \begin{bmatrix} 1 & 2 \\ 3 & 4 \end{bmatrix} \begin{bmatrix} 2 & 0 \\ 1 & 2 \end{bmatrix} = \begin{bmatrix} 1\times2 + 2\times1 & 1\times0 + 2\times2 \\ 3\times2 + 4\times1 & 3\times0 + 4\times2 \end{bmatrix} = \begin{bmatrix} 4 & 4 \\ 10 & 8 \end{bmatrix}. The trace of a matrix is the sum of its diagonal elements: 4+8=124 + 8 = 12.

A.

[3478]\begin{bmatrix} -3 & -4 \\ 7 & 8 \end{bmatrix}

B.

[19224350]\begin{bmatrix} 19 & 22 \\ 43 & 50 \end{bmatrix}

C.

[1001]\begin{bmatrix} 1 & 0 \\ 0 & 1 \end{bmatrix}

D.

[2112]\begin{bmatrix} 2 & 1 \\ 1 & 2 \end{bmatrix}
Correct Answer: A

Solution:

To find XX, solve the equation X=BA1X = B \cdot A^{-1}. Calculate the inverse of AA and then multiply it by BB.

A.

[63466969623]\begin{bmatrix} 63 & 46 & 69 \\ 69 & -6 & 23 \end{bmatrix}

B.

[69623634669]\begin{bmatrix} 69 & -6 & 23 \\ 63 & 46 & 69 \end{bmatrix}

C.

[46696362369]\begin{bmatrix} 46 & 69 & 63 \\ -6 & 23 & 69 \end{bmatrix}

D.

[23694669236]\begin{bmatrix} 23 & 69 & 46 \\ 69 & 23 & -6 \end{bmatrix}
Correct Answer: A

Solution:

From the given excerpt, A3=[63466969623]A^3 = \begin{bmatrix} 63 & 46 & 69 \\ 69 & -6 & 23 \end{bmatrix}.

A.

True, the equation holds.

B.

False, the equation does not hold.

C.

Cannot be determined from the given information.

D.

None of above is valid answer
Correct Answer: A

Solution:

Calculate A3A^3, then subtract 23A23A and 40I40I. The resulting matrix should be the zero matrix, confirming the equation holds.

A.

[0110]\begin{bmatrix} 0 & 1 \\ 1 & 0 \end{bmatrix}

B.

[1001]\begin{bmatrix} 1 & 0 \\ 0 & 1 \end{bmatrix}

C.

[1100]\begin{bmatrix} 1 & 1 \\ 0 & 0 \end{bmatrix}

D.

[0011]\begin{bmatrix} 0 & 0 \\ 1 & 1 \end{bmatrix}
Correct Answer: A

Solution:

The product AB=[0110]AB = \begin{bmatrix} 0 & 1 \\ 1 & 0 \end{bmatrix} is calculated by multiplying corresponding elements and summing them.

A.

₹62,000

B.

₹61,000

C.

₹60,000

D.

₹59,000
Correct Answer: A

Solution:

The total revenue from Market I is calculated as follows: 10,000×2.50+2,000×1.50+18,000×1.00=25,000+3,000+18,000=46,00010,000 \times 2.50 + 2,000 \times 1.50 + 18,000 \times 1.00 = 25,000 + 3,000 + 18,000 = 46,000. Therefore, the total revenue is ₹62,000.

A.

[681012]\begin{bmatrix} 6 & 8 \\ 10 & 12 \end{bmatrix}

B.

[5678]\begin{bmatrix} 5 & 6 \\ 7 & 8 \end{bmatrix}

C.

[1234]\begin{bmatrix} 1 & 2 \\ 3 & 4 \end{bmatrix}

D.

[0000]\begin{bmatrix} 0 & 0 \\ 0 & 0 \end{bmatrix}
Correct Answer: A

Solution:

To find the sum of two matrices, add the corresponding elements. So, A+B=[1+52+63+74+8]=[681012]A + B = \begin{bmatrix} 1+5 & 2+6 \\ 3+7 & 4+8 \end{bmatrix} = \begin{bmatrix} 6 & 8 \\ 10 & 12 \end{bmatrix}.

A.

3 Tall: 1 Dwarf

B.

1 Tall: 3 Dwarf

C.

2 Tall: 2 Dwarf

D.

4 Tall: 0 Dwarf
Correct Answer: A

Solution:

The phenotypic ratio in the F2 generation is 3 Tall: 1 Dwarf as per Mendel's principles.

A.

[150015]\begin{bmatrix} \frac{1}{5} & 0 \\ 0 & \frac{1}{5} \end{bmatrix}

B.

[5005]\begin{bmatrix} 5 & 0 \\ 0 & 5 \end{bmatrix}

C.

[1001]\begin{bmatrix} 1 & 0 \\ 0 & 1 \end{bmatrix}

D.

[0550]\begin{bmatrix} 0 & 5 \\ 5 & 0 \end{bmatrix}
Correct Answer: A

Solution:

The inverse of a diagonal matrix [a00b]\begin{bmatrix} a & 0 \\ 0 & b \end{bmatrix} is [1a001b]\begin{bmatrix} \frac{1}{a} & 0 \\ 0 & \frac{1}{b} \end{bmatrix}. Therefore, the inverse of A=[5005]A = \begin{bmatrix} 5 & 0 \\ 0 & 5 \end{bmatrix} is [150015]\begin{bmatrix} \frac{1}{5} & 0 \\ 0 & \frac{1}{5} \end{bmatrix}.

A.

2

B.

3

C.

5

D.

Both option_a and option_b
Correct Answer: D

Solution:

The characteristic equation A25A+6I=0A^2 - 5A + 6I = 0 can be factored as (A2I)(A3I)=0(A - 2I)(A - 3I) = 0. Therefore, the eigenvalues of AA are 2 and 3.

A.

AB is always symmetric

B.

AB is always skew-symmetric

C.

AB is symmetric if and only if A and B commute

D.

AB is neither symmetric nor skew-symmetric
Correct Answer: C

Solution:

For AB to be symmetric, it must hold that (AB)' = AB. Since A and B are symmetric, this implies AB = BA.

A.

10

B.

12

C.

14

D.

16
Correct Answer: A

Solution:

First, calculate C=A+B=[1+22+03+14+2]=[3246]C = A + B = \begin{bmatrix} 1+2 & 2+0 \\ 3+1 & 4+2 \end{bmatrix} = \begin{bmatrix} 3 & 2 \\ 4 & 6 \end{bmatrix}. The determinant of CC is 3×62×4=188=103 \times 6 - 2 \times 4 = 18 - 8 = 10.

A.

[5864139154]\begin{bmatrix} 58 & 64 \\ 139 & 154 \end{bmatrix}

B.

[5864139150]\begin{bmatrix} 58 & 64 \\ 139 & 150 \end{bmatrix}

C.

[5862139154]\begin{bmatrix} 58 & 62 \\ 139 & 154 \end{bmatrix}

D.

[5864140154]\begin{bmatrix} 58 & 64 \\ 140 & 154 \end{bmatrix}
Correct Answer: A

Solution:

The product AB=[5864139154]AB = \begin{bmatrix} 58 & 64 \\ 139 & 154 \end{bmatrix} is calculated by multiplying corresponding elements and summing them.

A.

3

B.

6

C.

0

D.

9
Correct Answer: B

Solution:

The trace of a matrix is the sum of its diagonal elements. So, the trace of AA is 3+3=63 + 3 = 6.

A.

[2435]\begin{bmatrix} 2 & 4 \\ 3 & 5 \end{bmatrix}

B.

[3254]\begin{bmatrix} 3 & 2 \\ 5 & 4 \end{bmatrix}

C.

[5432]\begin{bmatrix} 5 & 4 \\ 3 & 2 \end{bmatrix}

D.

[4253]\begin{bmatrix} 4 & 2 \\ 5 & 3 \end{bmatrix}
Correct Answer: A

Solution:

The transpose of a matrix is obtained by swapping its rows and columns. Thus, the transpose of A=[2345]A = \begin{bmatrix} 2 & 3 \\ 4 & 5 \end{bmatrix} is [2435]\begin{bmatrix} 2 & 4 \\ 3 & 5 \end{bmatrix}.

A.

[28615]\begin{bmatrix} 2 & 8 \\ 6 & 15 \end{bmatrix}

B.

[1425]\begin{bmatrix} 1 & 4 \\ 2 & 5 \end{bmatrix}

C.

[2003]\begin{bmatrix} 2 & 0 \\ 0 & 3 \end{bmatrix}

D.

[0000]\begin{bmatrix} 0 & 0 \\ 0 & 0 \end{bmatrix}
Correct Answer: A

Solution:

The product of two matrices is obtained by multiplying rows by columns. Thus, AB=[2×1+0×22×4+0×50×1+3×20×4+3×5]=[28615]AB = \begin{bmatrix} 2\times1 + 0\times2 & 2\times4 + 0\times5 \\ 0\times1 + 3\times2 & 0\times4 + 3\times5 \end{bmatrix} = \begin{bmatrix} 2 & 8 \\ 6 & 15 \end{bmatrix}.

A.

Matrix AA is invertible.

B.

Matrix AA is a zero matrix.

C.

Matrix AA is a scalar matrix.

D.

Matrix AA is a singular matrix.
Correct Answer: D

Solution:

Matrix AA is singular because its determinant is zero: det(A)=2(6)(3)(4)=12+12=0\det(A) = 2(-6) - (-3)(4) = -12 + 12 = 0.

A.

₹ 1200

B.

₹ 7000

C.

₹ 7100

D.

₹ 7200
Correct Answer: D

Solution:

The total cost for city Y is calculated by multiplying the matrix A by the second row of matrix B: 40×3000+100×1000+50×10000=720040 \times 3000 + 100 \times 1000 + 50 \times 10000 = 7200 paise, which is ₹ 7200.

A.

₹50,000

B.

₹45,000

C.

₹47,000

D.

₹48,000
Correct Answer: D

Solution:

The total revenue in Market I is calculated as follows: (10,000 * 2.50) + (2,000 * 1.50) + (18,000 * 1.00) = ₹48,000.

A.

If AB=BAAB = BA

B.

If AA and BB are both diagonal matrices

C.

If AA or BB is a zero matrix

D.

If AB=0AB = 0
Correct Answer: A

Solution:

For the product ABAB to be symmetric, it must hold that AB=BAAB = BA.

A.

A2=IA^2 = I, the identity matrix.

B.

A2=IA^2 = -I, the negative identity matrix.

C.

A2=AA^2 = A.

D.

A2=AA^2 = -A.
Correct Answer: A

Solution:

Calculating A2A^2: A2=[0110][0110]=[1001]=IA^2 = \begin{bmatrix} 0 & 1 \\ -1 & 0 \end{bmatrix} \begin{bmatrix} 0 & 1 \\ -1 & 0 \end{bmatrix} = \begin{bmatrix} 1 & 0 \\ 0 & 1 \end{bmatrix} = I.

A.

A is a diagonal matrix

B.

A is a zero matrix

C.

A is a square matrix

D.

None of these
Correct Answer: B

Solution:

A matrix that is both symmetric (A=ATA = A^T) and skew-symmetric (A=ATA = -A^T) must satisfy A=AA = -A, which implies 2A=02A = 0. Hence, AA must be a zero matrix.

A.

25

B.

50

C.

75

D.

100
Correct Answer: A

Solution:

The genotypic ratio of the F2 generation is 1 TT : 2 Tt : 1 tt. The number of homozygous recessive plants (tt) is 1/4 of the total, which is 1/4 of 100 = 25 plants.

A.

₹ 10,000 in 5% bonds and ₹ 20,000 in 7% bonds

B.

₹ 15,000 in each bond

C.

₹ 20,000 in 5% bonds and ₹ 10,000 in 7% bonds

D.

₹ 12,000 in 5% bonds and ₹ 18,000 in 7% bonds
Correct Answer: A

Solution:

Let x be the amount invested in 5% bonds and y in 7% bonds. We have x + y = ₹ 30,000 and 0.05x + 0.07y = ₹ 2000. Solving these equations gives x = ₹ 10,000 and y = ₹ 20,000.

A.

1:2:1

B.

3:1

C.

1:3

D.

2:1:1
Correct Answer: A

Solution:

In Mendel's monohybrid cross, the F2 generation shows a genotypic ratio of 1 homozygous dominant (TT) : 2 heterozygous (Tt) : 1 homozygous recessive (tt), which corresponds to the phenotypic ratio of 3 tall : 1 dwarf.

True or False

Correct Answer: False

Solution:

The product of two symmetric matrices AA and BB is symmetric if and only if AA and BB commute, i.e., AB=BAAB = BA. Otherwise, ABAB is not necessarily symmetric.

Correct Answer: True

Solution:

Given A2=AA^2 = A, we have (I+A)3=I+3A+3A2+A3=I+3A+3A+A=I+7A(I + A)^3 = I + 3A + 3A^2 + A^3 = I + 3A + 3A + A = I + 7A. Therefore, (I+A)37A=I(I + A)^3 - 7A = I.

Correct Answer: True

Solution:

Mendel's monohybrid cross experiment results in a phenotypic ratio of 3 tall plants to 1 dwarf plant in the F2 generation.

Correct Answer: False

Solution:

A rectangular matrix does not possess an inverse because for the inverse to exist, the matrix must be square.

Correct Answer: True

Solution:

A matrix that is both symmetric and skew-symmetric must have all its elements as zero, because the only way for A=AA = A' and A=AA = -A' to hold simultaneously is if all elements of AA are zero.

Correct Answer: False

Solution:

The correct formula for the inverse of a product of two invertible matrices is (AB)1=B1A1(AB)^{-1} = B^{-1}A^{-1}, not A1B1A^{-1}B^{-1}.

Correct Answer: True

Solution:

The matrix F(x)F(x) represents a rotation matrix. The property F(x)F(y)=F(x+y)F(x)F(y) = F(x + y) holds for rotation matrices, as it reflects the addition of angles.

Correct Answer: True

Solution:

Theorem 3 states that the inverse of a square matrix, if it exists, is unique. This is because if BB and CC are both inverses of AA, then B=CB = C.

Correct Answer: True

Solution:

A matrix AA is symmetric if A=AA' = A, meaning the transpose of AA is equal to AA itself.

Correct Answer: True

Solution:

If AA is symmetric, then BABB'AB is symmetric. This is because the symmetry of AA ensures that the product BABB'AB retains symmetry.

Correct Answer: True

Solution:

For any square matrix AA, the transpose of the transpose of AA is AA itself, i.e., (A)=A(A')' = A. This is a fundamental property of matrix transposition.

Correct Answer: True

Solution:

The given matrix AA is such that its transpose AA' is equal to AA, hence (A)=A(A')' = A holds true.

Correct Answer: True

Solution:

The transpose of a sum of matrices is the sum of their transposes, i.e., (A+B)=A+B(A + B)' = A' + B'. This property holds for any matrices AA and BB.

Correct Answer: True

Solution:

For symmetric matrices AA and BB, the product ABAB is symmetric if AB=BAAB = BA. Therefore, ABBAAB - BA is skew-symmetric because (ABBA)=(ABBA)(AB - BA)' = - (AB - BA).

Correct Answer: True

Solution:

The solution provided shows that for A=[321421101]A = \begin{bmatrix} 3 & -2 & 1 \\ 4 & 2 & 1 \\ 1 & 0 & 1 \end{bmatrix}, A323A40I=OA^3 - 23A - 40I = O is verified.

Correct Answer: True

Solution:

The equation A323A40I=OA^3 - 23A - 40I = O is a matrix equation that AA satisfies, meaning that when AA is substituted into the equation, it results in the zero matrix.

Correct Answer: True

Solution:

A matrix AA is called idempotent if A2=AA^2 = A. Therefore, by definition, if A2=AA^2 = A, AA is idempotent.

Correct Answer: True

Solution:

For ABAB to be symmetric, it must hold that (AB)=AB(AB)' = AB. Since AA and BB are symmetric, A=AA' = A and B=BB' = B. Therefore, (AB)=BA=BA(AB)' = B'A' = BA. Thus, ABAB is symmetric if and only if AB=BAAB = BA.

Correct Answer: True

Solution:

By definition, a zero matrix is one where all elements are zero.

Descriptive Questions

Expected Answer:
The total revenue for each market calculated using matrix multiplication.

Detailed Solution:

Represent the sales quantities and prices as matrices and perform matrix multiplication to find the total revenue for each market.

Expected Answer:
The total cost in city X is ₹340,000, and in city Y is ₹720,000. Matrices simplify the calculation of total costs by organizing data and operations efficiently, especially when dealing with large datasets.

Detailed Solution:

Compute AB=[4010050][100030005001000500010000]=[40×1000+100×500+50×500040×3000+100×1000+50×10000]=[340,000720,000]AB = \begin{bmatrix} 40 \\ 100 \\ 50 \end{bmatrix} \begin{bmatrix} 1000 & 3000 \\ 500 & 1000 \\ 5000 & 10000 \end{bmatrix} = \begin{bmatrix} 40 \times 1000 + 100 \times 500 + 50 \times 5000 & 40 \times 3000 + 100 \times 1000 + 50 \times 10000 \end{bmatrix} = \begin{bmatrix} 340,000 & 720,000 \end{bmatrix}.

Expected Answer:
The property (AB)1=B1A1(AB)^{-1} = B^{-1}A^{-1} is significant because it shows how the inverse of a product of matrices is related to the inverses of the individual matrices, which is useful in solving systems of linear equations.

Detailed Solution:

First, compute AB=[5123]×[1001]=[5123]AB = \begin{bmatrix} 5 & -1 \\ 2 & 3 \end{bmatrix} \times \begin{bmatrix} 1 & 0 \\ 0 & 1 \end{bmatrix} = \begin{bmatrix} 5 & -1 \\ 2 & 3 \end{bmatrix}. The inverse of BB is B1=[1001]B^{-1} = \begin{bmatrix} 1 & 0 \\ 0 & 1 \end{bmatrix}, and the inverse of AA is A1=1(5)(3)(1)(2)[3125]=117[3125]A^{-1} = \frac{1}{(5)(3) - (-1)(2)} \begin{bmatrix} 3 & 1 \\ -2 & 5 \end{bmatrix} = \frac{1}{17} \begin{bmatrix} 3 & 1 \\ -2 & 5 \end{bmatrix}. Thus, B1A1=[1001]×117[3125]=117[3125]B^{-1}A^{-1} = \begin{bmatrix} 1 & 0 \\ 0 & 1 \end{bmatrix} \times \frac{1}{17} \begin{bmatrix} 3 & 1 \\ -2 & 5 \end{bmatrix} = \frac{1}{17} \begin{bmatrix} 3 & 1 \\ -2 & 5 \end{bmatrix}. Therefore, (AB)1=B1A1(AB)^{-1} = B^{-1}A^{-1}, confirming the property.

Expected Answer:
The inverse of the product of two matrices is equal to the product of the inverses of the matrices in reverse order.

Detailed Solution:

To prove (AB)1=B1A1(AB)^{-1} = B^{-1}A^{-1}, we use the property of matrix inverses. Since AA and BB are invertible, ABAB is also invertible. By definition, (AB)(AB)1=I(AB)(AB)^{-1} = I. Pre-multiply both sides by A1A^{-1}: A1(AB)(AB)1=A1IA^{-1}(AB)(AB)^{-1} = A^{-1}I. Simplifying, (A1A)B(AB)1=A1(A^{-1}A)B(AB)^{-1} = A^{-1}, which gives IB(AB)1=A1IB(AB)^{-1} = A^{-1}, or B(AB)1=A1B(AB)^{-1} = A^{-1}. Pre-multiply by B1B^{-1}: B1B(AB)1=B1A1B^{-1}B(AB)^{-1} = B^{-1}A^{-1}, resulting in (AB)1=B1A1(AB)^{-1} = B^{-1}A^{-1}.

Expected Answer:
In Mendel's monohybrid cross experiment, the F2 generation shows a phenotypic ratio of 3 tall plants to 1 dwarf plant and a genotypic ratio of 1 homozygous tall (TT), 2 heterozygous tall (Tt), and 1 homozygous dwarf (tt).

Detailed Solution:

The F1 generation, obtained by crossing homozygous tall (TT) with homozygous dwarf (tt), results in all heterozygous tall (Tt) plants. Self-pollinating the F1 generation (Tt x Tt) produces the F2 generation. Using a Punnett square, the possible genotypes are TT, Tt, Tt, and tt, leading to a phenotypic ratio of 3 tall:1 dwarf and a genotypic ratio of 1 TT:2 Tt:1 tt.

Expected Answer:
Compute AB=[19224350]AB = \begin{bmatrix} 19 & 22 \\ 43 & 50 \end{bmatrix} and BA=[23343146]BA = \begin{bmatrix} 23 & 34 \\ 31 & 46 \end{bmatrix}. Matrix multiplication is not commutative, meaning ABBAAB \neq BA. This non-commutativity is crucial in many applications, such as transformations in graphics, where the order of operations affects the outcome.

Detailed Solution:

Calculate AB=[1×5+2×71×6+2×83×5+4×73×6+4×8]=[19224350]AB = \begin{bmatrix} 1 \times 5 + 2 \times 7 & 1 \times 6 + 2 \times 8 \\ 3 \times 5 + 4 \times 7 & 3 \times 6 + 4 \times 8 \end{bmatrix} = \begin{bmatrix} 19 & 22 \\ 43 & 50 \end{bmatrix}. Similarly, BA=[5×1+6×35×2+6×47×1+8×37×2+8×4]=[23343146]BA = \begin{bmatrix} 5 \times 1 + 6 \times 3 & 5 \times 2 + 6 \times 4 \\ 7 \times 1 + 8 \times 3 & 7 \times 2 + 8 \times 4 \end{bmatrix} = \begin{bmatrix} 23 & 34 \\ 31 & 46 \end{bmatrix}.

Expected Answer:
The equation A323A40I=OA^3 - 23A - 40I = O demonstrates that AA satisfies its own characteristic equation, which is a consequence of the Cayley-Hamilton theorem.

Detailed Solution:

Compute A2=A×A=[321421]×[321421]=[1461514615]A^2 = A \times A = \begin{bmatrix} 3 & -2 & 1 \\ 4 & 2 & 1 \end{bmatrix} \times \begin{bmatrix} 3 & -2 & 1 \\ 4 & 2 & 1 \end{bmatrix} = \begin{bmatrix} 14 & 6 & 15 \\ 14 & 6 & 15 \end{bmatrix}. Then, A3=A×A2=[321421]×[1461514615]=[634669924663]A^3 = A \times A^2 = \begin{bmatrix} 3 & -2 & 1 \\ 4 & 2 & 1 \end{bmatrix} \times \begin{bmatrix} 14 & 6 & 15 \\ 14 & 6 & 15 \end{bmatrix} = \begin{bmatrix} 63 & 46 & 69 \\ 92 & 46 & 63 \end{bmatrix}. Now, calculate 23A=23×[321421]=[694623924623]23A = 23 \times \begin{bmatrix} 3 & -2 & 1 \\ 4 & 2 & 1 \end{bmatrix} = \begin{bmatrix} 69 & -46 & 23 \\ 92 & 46 & 23 \end{bmatrix}. The identity matrix II is [100010]\begin{bmatrix} 1 & 0 & 0 \\ 0 & 1 & 0 \end{bmatrix}, so 40I=[40000400]40I = \begin{bmatrix} 40 & 0 & 0 \\ 0 & 40 & 0 \end{bmatrix}. Finally, A323A40I=[634669924663][694623924623][40000400]=[000000]=OA^3 - 23A - 40I = \begin{bmatrix} 63 & 46 & 69 \\ 92 & 46 & 63 \end{bmatrix} - \begin{bmatrix} 69 & -46 & 23 \\ 92 & 46 & 23 \end{bmatrix} - \begin{bmatrix} 40 & 0 & 0 \\ 0 & 40 & 0 \end{bmatrix} = \begin{bmatrix} 0 & 0 & 0 \\ 0 & 0 & 0 \end{bmatrix} = O. This confirms that A323A40I=OA^3 - 23A - 40I = O.

Expected Answer:
The expected answer should involve setting up matrices for quantities and prices, performing matrix multiplication to find total costs, and discussing the efficiency of matrices in handling such data.

Detailed Solution:

Represent the quantities as a matrix Q=[25810]Q = \begin{bmatrix} 2 & 5 \\ 8 & 10 \end{bmatrix} and prices as P1=[550]P_1 = \begin{bmatrix} 5 \\ 50 \end{bmatrix} and P2=[440]P_2 = \begin{bmatrix} 4 \\ 40 \end{bmatrix}. Calculate QP1Q \cdot P_1 and QP2Q \cdot P_2 to find total expenditures. Matrices streamline calculations by organizing data in a structured format, reducing computational errors.

Expected Answer:
To verify that (A)=A(A')' = A, compute the transpose of AA to obtain AA', and then compute the transpose of AA' to check if it equals AA.

Detailed Solution:

The transpose of AA is A=[423032]A' = \begin{bmatrix} 4 & 2 \\ 3 & 0 \\ \sqrt{3} & 2 \end{bmatrix}. The transpose of AA' is (A)=[433202](A')' = \begin{bmatrix} 4 & 3 & \sqrt{3} \\ 2 & 0 & 2 \end{bmatrix}, which is equal to AA. Thus, (A)=A(A')' = A is verified.

Expected Answer:
To verify the identity, compute A3A^3, 23A23A, and 40I40I, and then check if their combination results in the zero matrix. Such verifications are important as they confirm theoretical properties and ensure the correctness of mathematical models in applications.

Detailed Solution:

Calculate A3A^3, 23A23A, and 40I40I. Then, A323A40I=OA^3 - 23A - 40I = O. This confirms the identity, showing the consistency of matrix operations and their properties.

Expected Answer:
The transpose of a matrix sum is equal to the sum of the transposes of the matrices. Calculate (A+B)(A + B)' and A+BA' + B' to verify this property. A+B=[4332]+[1245]=[553+47].A + B = \begin{bmatrix} 4 & 3 \\ \sqrt{3} & 2 \end{bmatrix} + \begin{bmatrix} 1 & 2 \\ 4 & 5 \end{bmatrix} = \begin{bmatrix} 5 & 5 \\ \sqrt{3} + 4 & 7 \end{bmatrix}. Then, (A+B)=[53+457].(A + B)' = \begin{bmatrix} 5 & \sqrt{3} + 4 \\ 5 & 7 \end{bmatrix}. Now, A=[4332]A' = \begin{bmatrix} 4 & \sqrt{3} \\ 3 & 2 \end{bmatrix} and B=[1425].B' = \begin{bmatrix} 1 & 4 \\ 2 & 5 \end{bmatrix}. Therefore, A+B=[53+457]=(A+B).A' + B' = \begin{bmatrix} 5 & \sqrt{3} + 4 \\ 5 & 7 \end{bmatrix} = (A + B)'. This property is significant as it shows that transposition distributes over addition, which is important in simplifying expressions and proofs in linear algebra.

Detailed Solution:

Calculate the transpose of the sum and the sum of the transposes: A+B=[4332]+[1245]=[553+47].A + B = \begin{bmatrix} 4 & 3 \\ \sqrt{3} & 2 \end{bmatrix} + \begin{bmatrix} 1 & 2 \\ 4 & 5 \end{bmatrix} = \begin{bmatrix} 5 & 5 \\ \sqrt{3} + 4 & 7 \end{bmatrix}. Then, (A+B)=[53+457].(A + B)' = \begin{bmatrix} 5 & \sqrt{3} + 4 \\ 5 & 7 \end{bmatrix}. Now, A=[4332]A' = \begin{bmatrix} 4 & \sqrt{3} \\ 3 & 2 \end{bmatrix} and B=[1425].B' = \begin{bmatrix} 1 & 4 \\ 2 & 5 \end{bmatrix}. Therefore, A+B=[53+457]=(A+B).A' + B' = \begin{bmatrix} 5 & \sqrt{3} + 4 \\ 5 & 7 \end{bmatrix} = (A + B)'. This demonstrates that the transpose of a sum is the sum of the transposes.

Expected Answer:
The expected answer should show the multiplication of F(x)F(x) and F(y)F(y), resulting in F(x+y)F(x+y). This demonstrates that the matrices represent rotations, and their product corresponds to the composition of these rotations.

Detailed Solution:

Calculate F(x)F(y)F(x)F(y) and show it equals [cos(x+y)sin(x+y)0sin(x+y)cos(x+y)0001]\begin{bmatrix} \cos(x+y) & -\sin(x+y) & 0 \\ \sin(x+y) & \cos(x+y) & 0 \\ 0 & 0 & 1 \end{bmatrix}. This corresponds to a rotation matrix, showing that successive rotations are additive in angle, reflecting the composition of rotations.

Expected Answer:
For Market I, the revenue is 10000×2.50+2000×1.50+18000×1.00=4450010000 \times 2.50 + 2000 \times 1.50 + 18000 \times 1.00 = ₹44500. For Market II, the revenue is 6000×2.50+20000×1.50+8000×1.00=470006000 \times 2.50 + 20000 \times 1.50 + 8000 \times 1.00 = ₹47000. Total revenue is ₹91500.

Detailed Solution:

Calculate the revenue for Market I: 10000×2.50+2000×1.50+18000×1.00=25000+3000+18000=4450010000 \times 2.50 + 2000 \times 1.50 + 18000 \times 1.00 = ₹25000 + ₹3000 + ₹18000 = ₹44500. For Market II: 6000×2.50+20000×1.50+8000×1.00=15000+30000+8000=470006000 \times 2.50 + 20000 \times 1.50 + 8000 \times 1.00 = ₹15000 + ₹30000 + ₹8000 = ₹47000. Total revenue is ₹44500 + ₹47000 = ₹91500.

Expected Answer:
Calculate A+B=[681012]A + B = \begin{bmatrix} 6 & 8 \\ 10 & 12 \end{bmatrix}, then (A+B)C=[681012](A + B)C = \begin{bmatrix} 6 & 8 \\ 10 & 12 \end{bmatrix}. Separately, AC=AAC = A and BC=BBC = B, so AC+BC=A+B=[681012]AC + BC = A + B = \begin{bmatrix} 6 & 8 \\ 10 & 12 \end{bmatrix}. Therefore, (A+B)C=AC+BC(A + B)C = AC + BC.

Detailed Solution:

First, calculate A+B=[1+52+63+74+8]=[681012]A + B = \begin{bmatrix} 1+5 & 2+6 \\ 3+7 & 4+8 \end{bmatrix} = \begin{bmatrix} 6 & 8 \\ 10 & 12 \end{bmatrix}. Then, (A+B)C=[681012][1001]=[681012](A + B)C = \begin{bmatrix} 6 & 8 \\ 10 & 12 \end{bmatrix} \begin{bmatrix} 1 & 0 \\ 0 & 1 \end{bmatrix} = \begin{bmatrix} 6 & 8 \\ 10 & 12 \end{bmatrix}. Compute AC=A[1001]=AAC = A \begin{bmatrix} 1 & 0 \\ 0 & 1 \end{bmatrix} = A and BC=B[1001]=BBC = B \begin{bmatrix} 1 & 0 \\ 0 & 1 \end{bmatrix} = B. Thus, AC+BC=A+B=[681012]AC + BC = A + B = \begin{bmatrix} 6 & 8 \\ 10 & 12 \end{bmatrix}. Therefore, (A+B)C=AC+BC(A + B)C = AC + BC is verified.

Expected Answer:
The expected answer should conclude the properties of a matrix that is both symmetric and skew-symmetric.

Detailed Solution:

If a matrix AA is both symmetric and skew-symmetric, then AT=AA^T = A and AT=AA^T = -A. This implies that A=AA = -A, which can only be true if all elements of AA are zero. Therefore, AA must be a zero matrix.

Expected Answer:
The expected answer should involve showing that for symmetric matrices, the transpose of ABBAAB - BA is the negative of itself, thus proving it is skew-symmetric. The implications include insights into the behavior of linear transformations and their compositions.

Detailed Solution:

For symmetric matrices, A=AA' = A and B=BB' = B. Calculate (ABBA)=BAAB=BAAB=(ABBA)(AB - BA)' = B'A' - A'B' = BA - AB = -(AB - BA), proving skew-symmetry. This property is important in understanding the anti-commutative nature of certain matrix operations.

Expected Answer:
The expression simplifies to the zero matrix, confirming the identity.

Detailed Solution:

Calculate A3A^3, then compute 23A23A and 40I40I. Subtract these from A3A^3 and verify that the result is the zero matrix.

Expected Answer:
The expected answer is the total cost calculated using matrix multiplication.

Detailed Solution:

Multiply matrix AA by matrix BB to find the total cost in each city. The result will be a matrix indicating the total expenditure in cities X and Y.

Expected Answer:
The total cost in each city can be calculated by multiplying the matrices AA and BB. The resulting matrix is C=AB=[4010050][100030005001000500010000]=[40×1000+100×500+50×500040×3000+100×1000+50×10000]=[340000720000]C = A \cdot B = \begin{bmatrix} 40 \\ 100 \\ 50 \end{bmatrix} \cdot \begin{bmatrix} 1000 & 3000 \\ 500 & 1000 \\ 5000 & 10000 \end{bmatrix} = \begin{bmatrix} 40 \times 1000 + 100 \times 500 + 50 \times 5000 & 40 \times 3000 + 100 \times 1000 + 50 \times 10000 \end{bmatrix} = \begin{bmatrix} 340000 & 720000 \end{bmatrix}. Thus, the total cost in city X is ₹3400 and in city Y is ₹7200. Using matrices simplifies the computation by organizing data efficiently and allowing for systematic calculations.

Detailed Solution:

Perform matrix multiplication: C=AB=[40×1000+100×500+50×500040×3000+100×1000+50×10000]=[340000720000]C = A \cdot B = \begin{bmatrix} 40 \times 1000 + 100 \times 500 + 50 \times 5000 & 40 \times 3000 + 100 \times 1000 + 50 \times 10000 \end{bmatrix} = \begin{bmatrix} 340000 & 720000 \end{bmatrix}. The total cost in city X is ₹3400 and in city Y is ₹7200. Matrices provide a structured way to handle large datasets and perform complex calculations efficiently.

Expected Answer:
The expected answer should describe the genotypic and phenotypic ratios observed in the F2 generation of pea plants, based on Mendel's monohybrid cross experiment.

Detailed Solution:

In Mendel's monohybrid cross experiment, the parental generation consists of a tall plant (TT) and a dwarf plant (tt). The F1 generation, resulting from this cross, is all heterozygous tall (Tt). When the F1 generation is self-pollinated (Tt x Tt), the F2 generation results in a genotypic ratio of 1 TT : 2 Tt : 1 tt. This corresponds to a phenotypic ratio of 3 tall plants to 1 dwarf plant.

Expected Answer:
The expected answer should use matrix equations to allocate funds between the two bonds to achieve the specified interest. It should discuss how the allocation affects the risk and return profile of the investment.

Detailed Solution:

Let xx be the amount in the 5% bond and yy in the 7% bond. Set up the equation 0.05x+0.07y=18000.05x + 0.07y = 1800 with x+y=30000x + y = 30000. Solve the system to find x=18000x = 18000 and y=12000y = 12000. This allocation balances the interest income with risk, as higher interest bonds might carry more risk.

Expected Answer:
First, compute (A+B)=[123312412]+[502425]=[17327105412](A + B) = \begin{bmatrix} 12 & -3 \\ 3 & -12 \\ 4 & 12 \end{bmatrix} + \begin{bmatrix} 5 & 0 & 2 \\ 4 & 2 & 5 \end{bmatrix} = \begin{bmatrix} 17 & -3 & 2 \\ 7 & -10 & 5 \\ 4 & 12 \end{bmatrix}. Next, compute (BC)=[502425][032123]=[530342](B - C) = \begin{bmatrix} 5 & 0 & 2 \\ 4 & 2 & 5 \end{bmatrix} - \begin{bmatrix} 0 & 3 & 2 \\ 1 & -2 & 3 \end{bmatrix} = \begin{bmatrix} 5 & -3 & 0 \\ 3 & 4 & 2 \end{bmatrix}. Then, verify A+(BC)=(A+B)CA + (B - C) = (A + B) - C by computing both sides: A+(BC)=[123312412]+[530342]=[1760682412]A + (B - C) = \begin{bmatrix} 12 & -3 \\ 3 & -12 \\ 4 & 12 \end{bmatrix} + \begin{bmatrix} 5 & -3 & 0 \\ 3 & 4 & 2 \end{bmatrix} = \begin{bmatrix} 17 & -6 & 0 \\ 6 & -8 & 2 \\ 4 & 12 \end{bmatrix} and (A+B)C=[17327105412][032123]=[1760682412](A + B) - C = \begin{bmatrix} 17 & -3 & 2 \\ 7 & -10 & 5 \\ 4 & 12 \end{bmatrix} - \begin{bmatrix} 0 & 3 & 2 \\ 1 & -2 & 3 \end{bmatrix} = \begin{bmatrix} 17 & -6 & 0 \\ 6 & -8 & 2 \\ 4 & 12 \end{bmatrix}. Both results are equal, verifying the property. Verifying such properties ensures the correctness of matrix operations, which is crucial in applications involving complex matrix manipulations.

Detailed Solution:

Compute (A+B)=[17327105412](A + B) = \begin{bmatrix} 17 & -3 & 2 \\ 7 & -10 & 5 \\ 4 & 12 \end{bmatrix} and (BC)=[530342](B - C) = \begin{bmatrix} 5 & -3 & 0 \\ 3 & 4 & 2 \end{bmatrix}. Verify A+(BC)=(A+B)CA + (B - C) = (A + B) - C: A+(BC)=[1760682412]A + (B - C) = \begin{bmatrix} 17 & -6 & 0 \\ 6 & -8 & 2 \\ 4 & 12 \end{bmatrix} and (A+B)C=[1760682412](A + B) - C = \begin{bmatrix} 17 & -6 & 0 \\ 6 & -8 & 2 \\ 4 & 12 \end{bmatrix}. Both are equal, confirming the property. Verifying such properties is important for ensuring the accuracy of matrix operations in various applications.

Expected Answer:
The matrix A2A^2 should be calculated and then used to verify the given matrix equation.

Detailed Solution:

First, calculate A2=AA=[123456789][123456789]=[303642668196102126150]A^2 = A \cdot A = \begin{bmatrix} 1 & 2 & 3 \\ 4 & 5 & 6 \\ 7 & 8 & 9 \end{bmatrix} \begin{bmatrix} 1 & 2 & 3 \\ 4 & 5 & 6 \\ 7 & 8 & 9 \end{bmatrix} = \begin{bmatrix} 30 & 36 & 42 \\ 66 & 81 & 96 \\ 102 & 126 & 150 \end{bmatrix}. Now, calculate 5A=5[123456789]=[51015202530354045]5A = 5 \begin{bmatrix} 1 & 2 & 3 \\ 4 & 5 & 6 \\ 7 & 8 & 9 \end{bmatrix} = \begin{bmatrix} 5 & 10 & 15 \\ 20 & 25 & 30 \\ 35 & 40 & 45 \end{bmatrix} and 6I=6[100010001]=[600060006]6I = 6 \begin{bmatrix} 1 & 0 & 0 \\ 0 & 1 & 0 \\ 0 & 0 & 1 \end{bmatrix} = \begin{bmatrix} 6 & 0 & 0 \\ 0 & 6 & 0 \\ 0 & 0 & 6 \end{bmatrix}. Then, calculate A25A+6I=[303642668196102126150][51015202530354045]+[600060006]=[000000000]A^2 - 5A + 6I = \begin{bmatrix} 30 & 36 & 42 \\ 66 & 81 & 96 \\ 102 & 126 & 150 \end{bmatrix} - \begin{bmatrix} 5 & 10 & 15 \\ 20 & 25 & 30 \\ 35 & 40 & 45 \end{bmatrix} + \begin{bmatrix} 6 & 0 & 0 \\ 0 & 6 & 0 \\ 0 & 0 & 6 \end{bmatrix} = \begin{bmatrix} 0 & 0 & 0 \\ 0 & 0 & 0 \\ 0 & 0 & 0 \end{bmatrix}, which verifies the equation.

Expected Answer:
For ABAB to be symmetric, (AB)=AB(AB)' = AB. Since AA and BB are symmetric, A=AA' = A and B=BB' = B. Therefore, (AB)=BA=BA(AB)' = B'A' = BA. For AB=BAAB = BA, both sides must be equal, implying ABAB is symmetric if AB=BAAB = BA. This property is significant in linear transformations as it ensures the preservation of symmetry in compositions of transformations.

Detailed Solution:

To prove ABAB is symmetric if and only if AB=BAAB = BA: Assume ABAB is symmetric, then (AB)=AB(AB)' = AB. Since A=AA' = A and B=BB' = B, (AB)=BA=BA(AB)' = B'A' = BA. Hence, AB=BAAB = BA. Conversely, if AB=BAAB = BA, then (AB)=BA=AB(AB)' = BA = AB, so ABAB is symmetric. This result is important in linear transformations as it indicates when two transformations can be applied in any order without affecting symmetry.

Expected Answer:
The expected answer involves calculating the matrix products ACAC, BCBC, and (A+B)C(A + B)C, and verifying that (A+B)C=AC+BC(A + B)C = AC + BC.

Detailed Solution:

First, calculate AC=[608780][210]=[1214]AC = \begin{bmatrix} -6 & 0 & 8 \\ 7 & -8 & 0 \end{bmatrix} \begin{bmatrix} -2 \\ 1 \\ 0 \end{bmatrix} = \begin{bmatrix} 12 \\ -14 \end{bmatrix}. Next, calculate BC=[102278031][210]=[2163]BC = \begin{bmatrix} 1 & 0 & 2 \\ -2 & 7 & 8 \\ 0 & 3 & 1 \end{bmatrix} \begin{bmatrix} -2 \\ 1 \\ 0 \end{bmatrix} = \begin{bmatrix} -2 \\ 16 \\ 3 \end{bmatrix}. Then, calculate (A+B)C=[5010860][210]=[1012](A + B)C = \begin{bmatrix} -5 & 0 & 10 \\ 8 & -6 & 0 \end{bmatrix} \begin{bmatrix} -2 \\ 1 \\ 0 \end{bmatrix} = \begin{bmatrix} 10 \\ -12 \end{bmatrix}. Finally, verify that AC+BC=[1214]+[2163]=[1012]AC + BC = \begin{bmatrix} 12 \\ -14 \end{bmatrix} + \begin{bmatrix} -2 \\ 16 \\ 3 \end{bmatrix} = \begin{bmatrix} 10 \\ -12 \end{bmatrix}, confirming that (A+B)C=AC+BC(A + B)C = AC + BC.

Expected Answer:
Mendel's monohybrid cross experiment involves crossing two homozygous parents, one dominant (TT) and one recessive (tt). The F1 generation is all heterozygous (Tt) and phenotypically dominant. Self-pollinating F1 results in an F2 generation with a genotypic ratio of 1:2:1 (TT:Tt:tt) and a phenotypic ratio of 3:1 (dominant:recessive). This demonstrates the segregation of alleles and the predictable patterns of inheritance.

Detailed Solution:

In Mendel's experiment, the parental generation consists of TT (tall) and tt (dwarf) plants. The F1 generation, resulting from this cross, is all Tt and tall. When these F1 plants self-pollinate, the F2 generation consists of genotypes TT, Tt, Tt, and tt, giving a genotypic ratio of 1:2:1 and a phenotypic ratio of 3:1. The Punnett square visually represents these ratios, illustrating Mendel's laws of segregation and dominance. These principles are foundational in understanding genetic inheritance patterns.

Expected Answer:
In the F2 generation, the genotypic ratio is 1 TT : 2 Tt : 1 tt, and the phenotypic ratio is 3 Tall : 1 Dwarf. This experiment demonstrates Mendel's law of segregation, which states that alleles segregate independently during gamete formation, and each gamete carries only one allele for each trait. The F1 generation, being all Tt, shows the dominance of the tall trait, while the F2 generation reveals the segregation of alleles, resulting in a 3:1 phenotypic ratio.

Detailed Solution:

The F2 generation results from self-pollinating the F1 hybrids (Tt x Tt). The Punnett square for the F2 generation shows the combinations: TT, Tt, Tt, tt. The genotypic ratio is 1 TT : 2 Tt : 1 tt, and the phenotypic ratio is 3 Tall : 1 Dwarf. Mendel's laws are demonstrated as the alleles segregate independently, and the dominant allele masks the presence of the recessive allele in the heterozygous condition.

Expected Answer:
The total revenue in each market can be calculated by multiplying the sales matrix SS with the price matrix P=[2.51.51.0]P = \begin{bmatrix} 2.5 \\ 1.5 \\ 1.0 \end{bmatrix}. The resulting revenue matrix R=SP=[100006000200020000180008000][2.51.51.0]=[10000×2.5+2000×1.5+18000×1.06000×2.5+20000×1.5+8000×1.0]=[6400053000]R = S \cdot P = \begin{bmatrix} 10000 & 6000 \\ 2000 & 20000 \\ 18000 & 8000 \end{bmatrix} \cdot \begin{bmatrix} 2.5 \\ 1.5 \\ 1.0 \end{bmatrix} = \begin{bmatrix} 10000 \times 2.5 + 2000 \times 1.5 + 18000 \times 1.0 & 6000 \times 2.5 + 20000 \times 1.5 + 8000 \times 1.0 \end{bmatrix} = \begin{bmatrix} 64000 & 53000 \end{bmatrix}. Thus, the total revenue in market I is ₹64000 and in market II is ₹53000. Matrices simplify financial calculations by organizing data and allowing for efficient computation of total revenues across multiple markets.

Detailed Solution:

Perform matrix multiplication: R=SP=[10000×2.5+2000×1.5+18000×1.06000×2.5+20000×1.5+8000×1.0]=[6400053000]R = S \cdot P = \begin{bmatrix} 10000 \times 2.5 + 2000 \times 1.5 + 18000 \times 1.0 & 6000 \times 2.5 + 20000 \times 1.5 + 8000 \times 1.0 \end{bmatrix} = \begin{bmatrix} 64000 & 53000 \end{bmatrix}. The total revenue in market I is ₹64000 and in market II is ₹53000. Using matrices allows for efficient handling of large datasets and simplifies the computation of total revenues.

Expected Answer:
The transpose of a matrix is obtained by swapping rows with columns. For matrices AA and BB of appropriate dimensions, (A+B)=A+B(A + B)' = A' + B' holds because transposition is a linear operation.

Detailed Solution:

First, compute A+B=[4+13+23+42+2012+2]=[553+4414]A + B = \begin{bmatrix} 4+1 & 3+2 & \sqrt{3}+4 \\ 2+2 & 0-1 & 2+2 \end{bmatrix} = \begin{bmatrix} 5 & 5 & \sqrt{3}+4 \\ 4 & -1 & 4 \end{bmatrix}. The transpose of this matrix is (A+B)=[54513+44](A + B)' = \begin{bmatrix} 5 & 4 \\ 5 & -1 \\ \sqrt{3}+4 & 4 \end{bmatrix}. Now, A=[423032]A' = \begin{bmatrix} 4 & 2 \\ 3 & 0 \\ \sqrt{3} & 2 \end{bmatrix} and B=[122142]B' = \begin{bmatrix} 1 & 2 \\ 2 & -1 \\ 4 & 2 \end{bmatrix}. Adding these gives A+B=[4+12+23+2013+42+2]=[54513+44]A' + B' = \begin{bmatrix} 4+1 & 2+2 \\ 3+2 & 0-1 \\ \sqrt{3}+4 & 2+2 \end{bmatrix} = \begin{bmatrix} 5 & 4 \\ 5 & -1 \\ \sqrt{3}+4 & 4 \end{bmatrix}. Thus, (A+B)=A+B(A + B)' = A' + B', verifying the property.

Expected Answer:
The transpose of the sum of two matrices is equal to the sum of their transposes.

Detailed Solution:

To verify (A+B)=A+B(A + B)' = A' + B', first calculate A+BA + B and then find its transpose. Similarly, calculate the transpose of AA and BB separately and add them. Both should yield the same result.

Expected Answer:
The resulting matrix after performing the scalar multiplication and subtraction.

Detailed Solution:

Multiply matrix AA by 3 and matrix BB by 5. Subtract the resulting matrix of 5B5B from 3A3A to get the final matrix.

Expected Answer:
To verify the properties, we start by calculating the transpose of the matrices. The transpose of a matrix is obtained by swapping its rows and columns. For property 1, calculate A+BA + B and then find its transpose, (A+B)(A + B)'. Separately, find AA' and BB' and then compute A+BA' + B'. Show that these results are equal. For property 2, compute kBkB and then its transpose, (kB)(kB)'. Separately, find BB' and then kBkB'. Show that these results are equal. Discuss how transposition is used in applications such as rotating objects in computer graphics or transforming datasets in machine learning.

Detailed Solution:

  1. Calculate A+BA + B: A+B=[433202]+[124212]=[5543+212022]A + B = \begin{bmatrix} 4 & 3 \\ \sqrt{3} & 2 \\ 0 & 2 \end{bmatrix} + \begin{bmatrix} 1 & 2 & 4 \\ 2 & -1 & 2 \end{bmatrix} = \begin{bmatrix} 5 & 5 & 4 \\ \sqrt{3} + 2 & 1 & 2 \\ 0 & 2 & 2 \end{bmatrix} Now, find (A+B)(A + B)': (A+B)=[53+20512422](A + B)' = \begin{bmatrix} 5 & \sqrt{3} + 2 & 0 \\ 5 & 1 & 2 \\ 4 & 2 & 2 \end{bmatrix} Calculate AA' and BB': A=[430322]A' = \begin{bmatrix} 4 & \sqrt{3} & 0 \\ 3 & 2 & 2 \end{bmatrix} B=[122142]B' = \begin{bmatrix} 1 & 2 \\ 2 & -1 \\ 4 & 2 \end{bmatrix} Now, find A+BA' + B': A+B=[430322]+[122142]=[53+20512422]A' + B' = \begin{bmatrix} 4 & \sqrt{3} & 0 \\ 3 & 2 & 2 \end{bmatrix} + \begin{bmatrix} 1 & 2 \\ 2 & -1 \\ 4 & 2 \end{bmatrix} = \begin{bmatrix} 5 & \sqrt{3} + 2 & 0 \\ 5 & 1 & 2 \\ 4 & 2 & 2 \end{bmatrix} Thus, (A+B)=A+B(A + B)' = A' + B'. 2) For (kB)=kB(kB)' = kB', let k=3k = 3. Compute 3B3B: 3B=[3612636]3B = \begin{bmatrix} 3 & 6 & 12 \\ 6 & -3 & 6 \end{bmatrix} Now, find (3B)(3B)': (3B)=[3663126](3B)' = \begin{bmatrix} 3 & 6 \\ 6 & -3 \\ 12 & 6 \end{bmatrix} Compute 3B3B': 3B=3[122142]=[3663126]3B' = 3 \begin{bmatrix} 1 & 2 \\ 2 & -1 \\ 4 & 2 \end{bmatrix} = \begin{bmatrix} 3 & 6 \\ 6 & -3 \\ 12 & 6 \end{bmatrix} Thus, (3B)=3B(3B)' = 3B'. These properties demonstrate the linearity of transposition, which is crucial in simplifying complex matrix operations in various applications such as computer graphics for object transformations and data preprocessing in machine learning.

Expected Answer:
The expected answer should include the allocation of ₹30,000 between the two bonds to achieve the desired annual interest using matrix multiplication.

Detailed Solution:

Let xx be the amount invested in the first bond and yy be the amount invested in the second bond. We have the equations x+y=30,000x + y = 30,000 and 0.05x+0.07y=1,8000.05x + 0.07y = 1,800. Solving these equations, we express them in matrix form: [110.050.07][xy]=[30,0001,800]\begin{bmatrix} 1 & 1 \\ 0.05 & 0.07 \end{bmatrix} \begin{bmatrix} x \\ y \end{bmatrix} = \begin{bmatrix} 30,000 \\ 1,800 \end{bmatrix}. Solving this system, we find x=20,000x = 20,000 and y=10,000y = 10,000. Therefore, ₹20,000 should be invested in the first bond and ₹10,000 in the second bond.

Expected Answer:
In Mendel's monohybrid cross, the F1 generation is obtained by crossing homozygous tall (TT) and dwarf (tt) plants, resulting in all heterozygous tall (Tt) offspring. Self-pollination of F1 (Tt x Tt) results in an F2 generation with a phenotypic ratio of 3 tall:1 dwarf and a genotypic ratio of 1 TT:2 Tt:1 tt. The Punnett square shows these combinations.

Detailed Solution:

The F1 generation consists of heterozygous tall plants (Tt). When these are self-pollinated, the gametes are T and t. The Punnett square is: TtTTTTttTttt\begin{array}{c|c|c} & T & t \\ \hline T & TT & Tt \\ \hline t & Tt & tt \end{array}. The phenotypic ratio (3 tall:1 dwarf) arises because TT and Tt are tall, while tt is dwarf. The genotypic ratio (1 TT:2 Tt:1 tt) is directly from the Punnett square.

Expected Answer:
The expected answer should demonstrate that the product of symmetric matrices ABBAAB - BA results in a skew-symmetric matrix.

Detailed Solution:

To prove that ABBAAB - BA is skew-symmetric, we need to show that (ABBA)T=(ABBA)(AB - BA)^T = -(AB - BA). Since AA and BB are symmetric, we have AT=AA^T = A and BT=BB^T = B. Therefore, (ABBA)T=BTATATBT=BAAB=(ABBA)(AB - BA)^T = B^T A^T - A^T B^T = BA - AB = -(AB - BA). Thus, ABBAAB - BA is skew-symmetric.

Expected Answer:
The transpose of the sum of matrices AA and BB is equal to the sum of the transposes of AA and BB.

Detailed Solution:

First, calculate A+BA + B: A+B=[4+13+23+42+2012+2]=[553+4414]A + B = \begin{bmatrix} 4+1 & 3+2 & \sqrt{3}+4 \\ 2+2 & 0-1 & 2+2 \end{bmatrix} = \begin{bmatrix} 5 & 5 & \sqrt{3}+4 \\ 4 & -1 & 4 \end{bmatrix}. Then, find the transpose: (A+B)=[54513+44](A + B)' = \begin{bmatrix} 5 & 4 \\ 5 & -1 \\ \sqrt{3}+4 & 4 \end{bmatrix}. Now, calculate AA' and BB': A=[423032]A' = \begin{bmatrix} 4 & 2 \\ 3 & 0 \\ \sqrt{3} & 2 \end{bmatrix} and B=[122142]B' = \begin{bmatrix} 1 & 2 \\ 2 & -1 \\ 4 & 2 \end{bmatrix}. Sum the transposes: A+B=[4+12+23+2013+42+2]=[54513+44]A' + B' = \begin{bmatrix} 4+1 & 2+2 \\ 3+2 & 0-1 \\ \sqrt{3}+4 & 2+2 \end{bmatrix} = \begin{bmatrix} 5 & 4 \\ 5 & -1 \\ \sqrt{3}+4 & 4 \end{bmatrix}. Thus, (A+B)=A+B(A + B)' = A' + B'.

Expected Answer:
To verify (A)=A(A')' = A, we start by computing the transpose of AA, which is A=[423032]A' = \begin{bmatrix} 4 & 2 \\ 3 & 0 \\ \sqrt{3} & 2 \end{bmatrix}. The transpose of AA', denoted as (A)(A')', is calculated as [433202]\begin{bmatrix} 4 & 3 & \sqrt{3} \\ 2 & 0 & 2 \end{bmatrix}, which is identical to the original matrix AA. This property, that the transpose of the transpose of a matrix returns the original matrix, is fundamental in linear algebra as it ensures consistency in operations involving transpositions, such as in the computation of symmetric matrices or the adjoint of matrices.

Detailed Solution:

Compute the transpose of AA: A=[423032]A' = \begin{bmatrix} 4 & 2 \\ 3 & 0 \\ \sqrt{3} & 2 \end{bmatrix}. Then, compute the transpose of AA': (A)=[433202](A')' = \begin{bmatrix} 4 & 3 & \sqrt{3} \\ 2 & 0 & 2 \end{bmatrix}. Since (A)=A(A')' = A, the property is verified. This property is significant because it simplifies the manipulation of matrices, particularly in proofs and derivations involving matrix equations.

Expected Answer:
The product AB=[2345]AB = \begin{bmatrix} 2 & -3 \\ 4 & 5 \end{bmatrix} and BA=[2345]BA = \begin{bmatrix} 2 & -3 \\ 4 & 5 \end{bmatrix} are equal in this case because BB is the identity matrix. Generally, matrix multiplication is not commutative unless specific conditions are met, such as both matrices being diagonal or one being the identity matrix.

Detailed Solution:

To calculate ABAB, multiply AA and BB: AB=[2345][1001]=[2345]AB = \begin{bmatrix} 2 & -3 \\ 4 & 5 \end{bmatrix} \begin{bmatrix} 1 & 0 \\ 0 & 1 \end{bmatrix} = \begin{bmatrix} 2 & -3 \\ 4 & 5 \end{bmatrix}. Similarly, for BABA: BA=[1001][2345]=[2345]BA = \begin{bmatrix} 1 & 0 \\ 0 & 1 \end{bmatrix} \begin{bmatrix} 2 & -3 \\ 4 & 5 \end{bmatrix} = \begin{bmatrix} 2 & -3 \\ 4 & 5 \end{bmatrix}. The products are equal because BB is the identity matrix, which does not alter the other matrix. In general, AB=BAAB = BA only if AA and BB are both diagonal or one is the identity matrix.

Expected Answer:
The values of xx, yy, and zz that make the product of AA and its transpose equal to the identity matrix.

Detailed Solution:

Compute AA' and then AAA'A. Set the resulting matrix equal to the identity matrix and solve for xx, yy, and zz.

Expected Answer:
The expected answer should show the step-by-step calculation of A3A^3, 23A23A, and 40I40I, followed by their subtraction to arrive at the zero matrix. The significance lies in demonstrating a property of matrices where a polynomial expression of the matrix results in the zero matrix, indicating a characteristic polynomial.

Detailed Solution:

First, calculate A2=AAA^2 = A \cdot A, then A3=A2AA^3 = A^2 \cdot A. Compute 23A23A and 40I40I. Subtract these from A3A^3 to show the result is the zero matrix. This demonstrates a matrix polynomial identity, useful in understanding eigenvalues and characteristic polynomials.

Expected Answer:
The expected answer includes the combined sales matrix and the decrease in sales matrix.

Detailed Solution:

(i) Add matrices AA and BB to find the combined sales. (ii) Subtract matrix BB from matrix AA to find the decrease in sales.

Expected Answer:
The total revenue in Market I is ₹57,000 and in Market II is ₹49,000.

Detailed Solution:

For Market I, the revenue is 10,000×2.50+2,000×1.50+18,000×1.00=57,00010,000 \times 2.50 + 2,000 \times 1.50 + 18,000 \times 1.00 = ₹57,000. For Market II, the revenue is 6,000×2.50+20,000×1.50+8,000×1.00=49,0006,000 \times 2.50 + 20,000 \times 1.50 + 8,000 \times 1.00 = ₹49,000.

Expected Answer:
The product ACAC is calculated by taking the dot product of rows of AA with columns of CC. For example, the first element of ACAC is (6)(2)+(0)(12)+(8)(3)=12+24=36(-6)(-2) + (0)(12) + (8)(3) = 12 + 24 = 36. This process is repeated for each element of the resulting matrix. The verification of (A+B)C=AC+BC(A + B)C = AC + BC involves calculating (A+B)(A + B) first, then multiplying by CC, and comparing with the sum of ACAC and BCBC.

Detailed Solution:

To calculate ACAC, perform the following matrix multiplication: AC=[608780][2012032]=[(6)(2)+(0)(12)+(8)(3)(6)(0)+(0)(0)+(8)(2)(7)(2)+(8)(12)+(0)(3)(7)(0)+(8)(0)+(0)(2)]=[36161100].AC = \begin{bmatrix} -6 & 0 & 8 \\ 7 & -8 & 0 \end{bmatrix} \begin{bmatrix} -2 & 0 \\ 12 & 0 \\ 3 & 2 \end{bmatrix} = \begin{bmatrix} (-6)(-2) + (0)(12) + (8)(3) & (-6)(0) + (0)(0) + (8)(2) \\ (7)(-2) + (-8)(12) + (0)(3) & (7)(0) + (-8)(0) + (0)(2) \end{bmatrix} = \begin{bmatrix} 36 & 16 \\ -110 & 0 \end{bmatrix}. To verify (A+B)C=AC+BC(A + B)C = AC + BC, compute (A+B)(A + B), multiply by CC, and compare with AC+BCAC + BC. This property shows the distributive law of matrix multiplication, which is fundamental in linear algebra.