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Why numerical computation solves real problems in MATLAB - Test Your Understanding

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Practice - 5 Tasks
Answer the questions below
1fill in blank
easy

Complete the code to calculate the square root of 16.

MATLAB
result = sqrt([1]);
Drag options to blanks, or click blank then click option'
A4
B16
C8
D25
Attempts:
3 left
💡 Hint
Common Mistakes
Using the wrong number inside sqrt, like 25 or 8.
2fill in blank
medium

Complete the code to create a vector from 1 to 5.

MATLAB
vec = [1];
Drag options to blanks, or click blank then click option'
A1:10
Blinspace(1,10,5)
C[5 4 3 2 1]
D1:5
Attempts:
3 left
💡 Hint
Common Mistakes
Using 1:10 creates a longer vector than needed.
3fill in blank
hard

Fix the error in the code to compute the sum of elements in vector v.

MATLAB
total = [1](v);
Drag options to blanks, or click blank then click option'
Asum
Badd
Cplus
Dtotal
Attempts:
3 left
💡 Hint
Common Mistakes
Using add or plus which are not functions for summing vectors.
4fill in blank
hard

Fill both blanks to create a vector of squares of numbers 1 to 5.

MATLAB
squares = ([1]:[2]).^2;
Drag options to blanks, or click blank then click option'
A1
B2
C5
D10
Attempts:
3 left
💡 Hint
Common Mistakes
Using wrong start or end values like 2 or 10.
5fill in blank
hard

Fill all three blanks to create a vector of even numbers from 2 to 10.

MATLAB
evens = [1]:[2]:[3];
Drag options to blanks, or click blank then click option'
A1
B2
C10
D5
Attempts:
3 left
💡 Hint
Common Mistakes
Using step 1 instead of 2, or wrong start/end values.

Practice

(1/5)
1.

Why do we use numerical computation in MATLAB for real-world problems?

easy
A. Because numerical computation is always faster than exact math
B. Because MATLAB cannot handle symbolic math
C. Because exact math solutions are often impossible or too complex
D. Because numerical computation gives exact answers every time

Solution

  1. Step 1: Understand the nature of real-world problems

    Many real-world problems involve complex equations that cannot be solved exactly by hand or symbolic math.
  2. Step 2: Role of numerical computation

    Numerical computation approximates solutions using numbers and calculations, making it possible to find answers where exact math fails.
  3. Final Answer:

    Because exact math solutions are often impossible or too complex -> Option C
  4. Quick Check:

    Numerical computation solves complex problems [OK]
Hint: Numerical methods approximate when exact math is too hard [OK]
Common Mistakes:
  • Thinking numerical computation always gives exact answers
  • Believing MATLAB cannot do symbolic math
  • Assuming numerical computation is always faster
2.

Which MATLAB command correctly creates a vector of 100 linearly spaced points between 0 and 1?

?
easy
A. linspace(0, 1, 100)
B. range(0, 1, 100)
C. vector(0, 1, 100)
D. linspace(100, 0, 1)

Solution

  1. Step 1: Recall MATLAB function for linear spacing

    MATLAB's linspace creates linearly spaced vectors with syntax linspace(start, end, number_of_points).
  2. Step 2: Match the correct syntax

    The correct command is linspace(0, 1, 100) to get 100 points from 0 to 1.
  3. Final Answer:

    linspace(0, 1, 100) -> Option A
  4. Quick Check:

    linspace(start, end, n) = linspace(0,1,100) [OK]
Hint: Use linspace(start, end, count) for evenly spaced vectors [OK]
Common Mistakes:
  • Using range instead of linspace
  • Swapping start and end values
  • Using incorrect function names like vector
3.

What is the output of this MATLAB code?

x = linspace(0, 2, 5);
y = sin(pi * x);
y
medium
A. [0 1 0 -1 0]
B. [0 0.5 1 0.5 0]
C. [0 0.7071 1 0.7071 0]
D. [0 0.7071 0 -0.7071 0]

Solution

  1. Step 1: Calculate vector x values

    linspace(0, 2, 5) creates [0, 0.5, 1, 1.5, 2].
  2. Step 2: Compute y = sin(pi * x)

    Calculate sin(pi*0)=0, sin(pi*0.5)=1, sin(pi*1)=0, sin(pi*1.5)=-1, sin(pi*2)=0.
  3. Final Answer:

    [0 1 0 -1 0] -> Option A
  4. Quick Check:

    sin(pi * linspace(0,2,5)) = [0 1 0 -1 0] [OK]
Hint: Calculate linspace values first, then apply sin(pi * x) [OK]
Common Mistakes:
  • Confusing degrees and radians in sin function
  • Miscomputing linspace values
  • Using wrong function like cos instead of sin
4.

Identify the error in this MATLAB code snippet that tries to compute the square root of each element in vector A:

A = [4, 9, 16, 25];
B = sqrt A;
medium
A. sqrt function requires two arguments
B. Using square root on a vector is not allowed
C. Vector A should be a column vector
D. Missing parentheses around A in sqrt function

Solution

  1. Step 1: Check MATLAB function syntax

    Functions require parentheses around their arguments, so sqrt A is invalid syntax.
  2. Step 2: Correct the syntax

    Use sqrt(A) to compute element-wise square roots of vector A.
  3. Final Answer:

    Missing parentheses around A in sqrt function -> Option D
  4. Quick Check:

    Function calls need parentheses [OK]
Hint: Always use parentheses for function arguments in MATLAB [OK]
Common Mistakes:
  • Omitting parentheses in function calls
  • Thinking sqrt can't handle vectors
  • Assuming sqrt needs multiple arguments
5.

You want to approximate the integral of f(x) = exp(-x^2) from 0 to 1 using numerical computation in MATLAB. Which approach best solves this real problem?

hard
A. Manually calculate the exact integral using symbolic math
B. Use integral(@(x) exp(-x.^2), 0, 1) to compute the numerical integral
C. Use a for loop to sum exp(-x^2) at random points without spacing
D. Approximate by taking the value at x=0.5 only

Solution

  1. Step 1: Understand the integral problem

    The integral of exp(-x^2) has no simple exact formula, so numerical methods are needed.
  2. Step 2: Use MATLAB's numerical integration function

    The integral function with an anonymous function handles this efficiently and accurately.
  3. Final Answer:

    Use integral(@(x) exp(-x.^2), 0, 1) to compute the numerical integral -> Option B
  4. Quick Check:

    Numerical integration with integral() solves complex integrals [OK]
Hint: Use integral() with function handle for numerical integration [OK]
Common Mistakes:
  • Trying to find exact integral manually
  • Summing values at random points without spacing
  • Using a single point value as approximation
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