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Ignition Learning — Activity Sheet

Matrices

Mathematics · Year 11

Name: ______________________Date: ____________

A matrix is a rectangular grid of numbers, organised in rows and columns, used to represent and manipulate data efficiently — from transformations in graphics to solving systems of equations. Matrices can be added or subtracted if they're the same size, by combining corresponding entries. Matrix multiplication is more complex: it involves multiplying rows by columns, and is only possible when the number of columns in the first matrix matches the number of rows in the second.

Example

A matrix could represent a shop's weekly sales of two products across three days: [[12, 15, 9], [20, 18, 22]] — the first row for Product A and the second for Product B, with each column representing a day, making it easy to organise and later analyse the data.

Key terms

Matrix:
A rectangular grid of numbers organised in rows and columns.
Order (of a matrix):
The dimensions of a matrix, given as rows × columns.
Matrix multiplication:
Combining two matrices by multiplying rows by columns, under specific size rules.

Questions

  1. 1. A matrix is:

    • A rectangular grid of numbers organised in rows and columns
    • A single number only
    • A type of graph with no numbers
    • A type of triangle
  2. 2. The order of a matrix describes its:

    • Dimensions, given as rows × columns
    • Colour
    • Age
    • Total sum only
  3. 3. Matrices can be added if they are:

    • The same size
    • Any size at all, with no restriction
    • Always exactly 1×1
    • Never able to be added under any condition
  4. 4. A matrix with 2 rows and 3 columns has the order:

    • 2×3
    • 3×2
    • 5×5
    • 6×6
  5. 5. Adding two matrices involves:

    • Combining corresponding entries
    • Multiplying every entry by zero
    • Deleting one matrix entirely
    • Ignoring the numbers completely
  6. 6. Matrix multiplication involves:

    • Multiplying rows by columns
    • Only adding corresponding entries
    • Ignoring rows and columns entirely
    • Never combining any two matrices
  7. 7. Matrices are used to represent data such as:

    • Sales figures organised by product and day
    • Nothing measurable at all
    • Only single, standalone numbers
    • Only colours, with no numbers involved
  8. 8. For matrices A = [[1, 2], [3, 4]] and B = [[5, 6], [7, 8]], A + B equals:

    • [[6, 8], [10, 12]]
    • [[5, 6], [7, 8]]
    • [[1, 2], [3, 4]]
    • [[4, 4], [4, 4]]
  9. 9. For matrix A = [[2, 4], [6, 8]], A - [[1, 1], [1, 1]] equals:

    • [[1, 3], [5, 7]]
    • [[3, 5], [7, 9]]
    • [[2, 4], [6, 8]]
    • [[1, 1], [1, 1]]
  10. 10. Matrix multiplication between a 2×3 matrix and a 3×2 matrix is:

    • Possible, since the columns of the first match the rows of the second
    • Never possible under any circumstance
    • Only possible if both matrices are identical
    • Only possible with square matrices
  11. 11. Matrix multiplication between a 2×3 matrix and a 2×4 matrix is:

    • Not possible, since 3 does not match 2
    • Always possible regardless of size
    • Only possible for square matrices
    • The same as simple addition
  12. 12. A matrix showing two products sold across three days would have the order:

    • 2×3
    • 3×2
    • 2×2
    • 6×1
  13. 13. Why are matrices useful for organising real-world data, such as sales figures across multiple categories and time periods?

    • They compactly structure related data in rows and columns, making it easier to analyse and manipulate systematically
    • Matrices can only ever store a single number, with no structure
    • Organising data in a matrix always makes it harder to read
    • Matrices have no practical application outside of pure mathematics
  14. 14. Why does matrix multiplication require the number of columns in the first matrix to match the number of rows in the second?

    • Each entry in the resulting matrix comes from pairing a full row with a full column, so their lengths must align
    • This size requirement is a purely arbitrary rule with no mathematical basis
    • Matrix multiplication never has any size restrictions at all
    • Matrix addition and multiplication always follow identical size rules
  15. 15. Why might matrices be used in computer graphics to represent transformations like rotation or scaling of an image?

    • Matrix operations can systematically apply the same transformation to every point (pixel or vertex) in a consistent way
    • Matrices have no real connection to computer graphics or transformations
    • Transformations in graphics are always done manually, one pixel at a time
    • Only addition, never multiplication, is used in graphics transformations
  16. 16. Why is matrix addition considered simpler than matrix multiplication, from a computational standpoint?

    • Addition only combines corresponding entries directly, while multiplication requires combining entire rows and columns
    • Addition and multiplication of matrices require exactly the same amount of calculation
    • Matrix addition is actually more complex than matrix multiplication
    • Neither operation involves any meaningful calculation at all
  17. 17. Why might matrices be a natural way to represent and solve a system of simultaneous equations?

    • The coefficients and variables can be organised into matrices, allowing systematic methods to solve for unknowns
    • Matrices can never be used to represent equations of any kind
    • Simultaneous equations have no mathematical connection to matrices
    • Matrices can only represent numerical data, never algebraic relationships
  18. 18. For matrix A = [[3, 0], [1, 5]], multiplying every entry by 2 (scalar multiplication) gives:

    • [[6, 0], [2, 10]]
    • [[5, 2], [3, 7]]
    • [[3, 0], [1, 5]]
    • [[9, 0], [3, 15]]
  19. 19. Two matrices of different orders (e.g. a 2×2 and a 3×3) can be:

    • Multiplied only if the inner dimensions match, but never added or subtracted
    • Added directly with no restrictions at all
    • Combined using any operation with no rules whatsoever
    • Never used in any mathematical operation together
  20. 20. Why might a spreadsheet application be considered a practical, everyday example of matrix-like data organisation?

    • Rows and columns of related data can be systematically referenced and combined, just like in a matrix
    • Spreadsheets have no structural similarity to matrices at all
    • Matrices can only exist in formal mathematics, never in software
    • Spreadsheet data is always a single unstructured list, not a grid
  21. 21. Why might representing a network of city populations and their year-on-year change as a matrix make certain calculations more efficient?

    • Operations like scaling every value by a growth rate can be applied consistently across the whole matrix at once
    • Matrices always make simple calculations more complicated, not less
    • Matrices can only ever store a single unchanging value with no calculation possible
    • Efficient organisation of data has no connection to matrix representation

Answer key (parent copy)

  1. 1. A rectangular grid of numbers organised in rows and columns
  2. 2. Dimensions, given as rows × columns
  3. 3. The same size
  4. 4. 2×3
  5. 5. Combining corresponding entries
  6. 6. Multiplying rows by columns
  7. 7. Sales figures organised by product and day
  8. 8. [[6, 8], [10, 12]]
  9. 9. [[1, 3], [5, 7]]
  10. 10. Possible, since the columns of the first match the rows of the second
  11. 11. Not possible, since 3 does not match 2
  12. 12. 2×3
  13. 13. They compactly structure related data in rows and columns, making it easier to analyse and manipulate systematically
  14. 14. Each entry in the resulting matrix comes from pairing a full row with a full column, so their lengths must align
  15. 15. Matrix operations can systematically apply the same transformation to every point (pixel or vertex) in a consistent way
  16. 16. Addition only combines corresponding entries directly, while multiplication requires combining entire rows and columns
  17. 17. The coefficients and variables can be organised into matrices, allowing systematic methods to solve for unknowns
  18. 18. [[6, 0], [2, 10]]
  19. 19. Multiplied only if the inner dimensions match, but never added or subtracted
  20. 20. Rows and columns of related data can be systematically referenced and combined, just like in a matrix
  21. 21. Operations like scaling every value by a growth rate can be applied consistently across the whole matrix at once