Riemann Sum

Riemann Sum - Solve mathematical problems with step-by-step solutions.

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Riemann Sum Calculator

Approximate definite integrals using Riemann sums

Lower (a)

Upper (b)

Preset Functions

Riemann Sum

Approximates the area under a curve by dividing it into rectangles

Riemann Sum Methods

Left Riemann

Uses left endpoint of each interval (underestimate for increasing functions)

Right Riemann

Uses right endpoint of each interval (overestimate for increasing functions)

Midpoint Riemann

Uses midpoint of each interval (more accurate than left/right)

Trapezoidal

Uses trapezoids instead of rectangles (highly accurate method)

How the Riemann Sum Calculator Works

The Riemann Sum Calculator approximates the area under a curve by dividing the region into rectangles and summing their areas. This numerical integration method is fundamental to understanding definite integrals and provides the foundation for the Fundamental Theorem of Calculus. It's particularly useful when exact integration is difficult or impossible.

Understanding Riemann Sums

A Riemann sum approximates ∫ab f(x)dx by dividing [a,b] into n subintervals of width Δx = (b-a)/n, then summing the areas of rectangles: Σf(xi*)Δx, where xi* is a sample point in each subinterval. As n→∞, the Riemann sum approaches the exact integral value.

Types of Riemann Sums

  • Left Riemann Sum: Use the left endpoint of each subinterval: xi* = xi. Rectangle height is f(xi).
  • Right Riemann Sum: Use the right endpoint: xi* = xi+1. Rectangle height is f(xi+1).
  • Midpoint Riemann Sum: Use the midpoint: xi* = (xi + xi+1)/2. Generally more accurate than left or right.
  • Upper Sum: Use the maximum value of f on each subinterval (overestimates for positive functions).
  • Lower Sum: Use the minimum value of f on each subinterval (underestimates for positive functions).

The Formula

For n subintervals on [a,b] with Δx = (b-a)/n:

  • Left: Ln = Σi=0n-1 f(a + iΔx)·Δx
  • Right: Rn = Σi=1n f(a + iΔx)·Δx
  • Midpoint: Mn = Σi=1n f(a + (i-0.5)Δx)·Δx

Accuracy and Convergence

As the number of rectangles n increases, the approximation improves. The limit as n→∞ gives the exact integral value. For better accuracy with fewer rectangles, use the midpoint rule or more sophisticated methods like the Trapezoidal Rule or Simpson's Rule.

Examples

Riemann Sum Examples

Example 1: Left Riemann Sum

Problem: Approximate ∫02 x2dx using 4 rectangles (left endpoints)

Solution:

  • Δx = (2-0)/4 = 0.5
  • Subintervals: [0, 0.5], [0.5, 1], [1, 1.5], [1.5, 2]
  • Left endpoints: x = 0, 0.5, 1, 1.5
  • Sum: f(0)·0.5 + f(0.5)·0.5 + f(1)·0.5 + f(1.5)·0.5
  • = 0·0.5 + 0.25·0.5 + 1·0.5 + 2.25·0.5 = 1.75
  • (Exact value is 8/3 ≈ 2.667, so this underestimates)
Example 2: Right Riemann Sum

Problem: Approximate ∫02 x2dx using 4 rectangles (right endpoints)

Solution:

  • Δx = 0.5 (same as before)
  • Right endpoints: x = 0.5, 1, 1.5, 2
  • Sum: f(0.5)·0.5 + f(1)·0.5 + f(1.5)·0.5 + f(2)·0.5
  • = 0.25·0.5 + 1·0.5 + 2.25·0.5 + 4·0.5 = 3.75
  • (This overestimates since x2 is increasing)
Example 3: Midpoint Riemann Sum

Problem: Approximate ∫02 x2dx using 4 rectangles (midpoints)

Solution:

  • Δx = 0.5
  • Midpoints: x = 0.25, 0.75, 1.25, 1.75
  • Sum: f(0.25)·0.5 + f(0.75)·0.5 + f(1.25)·0.5 + f(1.75)·0.5
  • = 0.0625·0.5 + 0.5625·0.5 + 1.5625·0.5 + 3.0625·0.5
  • = 2.625
  • (Much closer to exact value of 2.667!)
Example 4: Increasing Accuracy

Problem: Show that more rectangles improve accuracy for ∫01 x3dx

Solution (Midpoint Rule):

  • Exact value: ∫01 x3dx = x4/4 |10 = 0.25
  • n=2 rectangles: M2 ≈ 0.2656 (error ≈ 0.016)
  • n=4 rectangles: M4 ≈ 0.2539 (error ≈ 0.004)
  • n=8 rectangles: M8 ≈ 0.2510 (error ≈ 0.001)
  • As n increases, error decreases and approximation improves
Example 5: Trigonometric Function

Problem: Approximate ∫0π/2 sin(x)dx using 3 rectangles (left endpoints)

Solution:

  • Δx = (π/2)/3 ≈ 0.524
  • Left endpoints: x = 0, π/6, π/3
  • f(0) = sin(0) = 0
  • f(π/6) = sin(π/6) = 0.5
  • f(π/3) = sin(π/3) ≈ 0.866
  • Sum ≈ (0 + 0.5 + 0.866)·0.524 ≈ 0.716
  • (Exact value is 1, so this underestimates)
Example 6: Average of Left and Right

Concept: The average of left and right Riemann sums equals the Trapezoidal Rule

For ∫02 x2dx with n=4:

  • Left sum: L4 = 1.75
  • Right sum: R4 = 3.75
  • Average: (1.75 + 3.75)/2 = 2.75
  • This equals the Trapezoidal Rule approximation
  • Closer to exact value (2.667) than either left or right alone

Tips & Best Practices

Tips for Computing Riemann Sums

  • Calculate Δx First: Always start by finding the width of each rectangle: Δx = (b-a)/n.
  • List Your Sample Points: Write out the x-values you'll use (left, right, or midpoints) before computing.
  • Organize Your Work: Create a table with columns for i, x_i, f(x_i), and f(x_i)·Δx for clarity.
  • Choose Midpoint for Better Accuracy: When possible, use the midpoint rule as it's generally more accurate than left or right.
  • Understand Over/Under Estimation: For increasing functions, left sums underestimate and right sums overestimate (reverse for decreasing).
  • Check Your Bounds: Make sure you're using the correct interval [a,b] and that a < b.
  • More Rectangles = Better Approximation: Doubling n typically reduces error significantly but requires more computation.
  • Compare Methods: Try both left and right sums; if they're close, the approximation is likely good.
  • Verify with Known Integrals: Practice with functions you can integrate exactly to understand approximation quality.
  • Use Technology Wisely: For large n, use calculators or computers, but understand the underlying method.

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