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IB DP Maths: AI SL

Revision Notes

Home / DP / Maths: AI SL / IB / Revision Notes / 3. Geometry & Trigonometry / 3.1 Geometry Toolkit / 3.1.2 Arcs & Sectors


3.1.2 Arcs & Sectors


Length of an Arc

What is an arc?

  • An arc is a part of the circumference of a circle
    • It is easiest to think of it as the crust of a single slice of pizza
  • The length of an arc depends of the size of the angle at the centre of the circle
  • If the angle at the centre is less than 180° then the arc is known as a minor arc
    • This could be considered as the crust of a single slice of pizza
  • If the angle at the centre is more than 180° then the arc is known as a major arc
    • This could be considered as the crust of the remaining pizza after a slice has been taken away

 

How do I find the length of an arc?

  • The length of an arc is simply a fraction of the circumference of a circle
    • The fraction can be found by dividing the angle at the centre by 360°
  • The formula for the length, l, of an arc is

begin mathsize 22px style l equals theta over 360 space space cross times 2 pi italic space r end style

    • Where theta is the angle measured in degrees
    • r is the radius
    • This is in the formula booklet, you do not need to remember it

Worked Example

A circular pizza has had a slice cut from it, the angle of the slice that was cut was 38 °. The radius of the pizza is 12 cm. Find

 

i)
the length of the outside crust of the slice of pizza (the minor arc),ai-sl-3-1-2-length-arc-we-i

 

ii)
the perimeter of the remaining pizza.ai-sl-3-1-2-length-arcwe-ii

Area of a Sector

What is a sector?

  • A sector is a part of a circle enclosed by two radii (radiuses) and an arc
    • It is easier to think of this as the shape of a single slice of pizza
  • The area of a sector depends of the size of the angle at the centre of the sector
  • If the angle at the centre is less than 180° then the sector is known as a minor sector
    • This could be considered as the shape of a single slice of pizza
  • If the angle at the centre is more than 180° then the sector is known as a major sector
    • This could be considered as the shape of the remaining pizza after a slice has been taken away

 

How do I find the area of a sector?

  • The area of a sector is simply a fraction of the area of the whole circle
    • The fraction can be found by dividing the angle at the centre by 360°
  • The formula for the area, A, of a sector is

begin mathsize 22px style A equals theta over 360 cross times pi r squared end style

    • Where theta is the angle measured in degrees
    • r is the radius
    • This is in the formula booklet, you do not need to remember it

Worked Example

Jamie has divided a circle of radius 50 cm into two sectors; a minor sector of angle 100° and a major sector of angle 260°. He is going to paint the minor sector blue and the major sector yellow. Find

i)
the area Jamie will paint blue,

ai-sl-3-1-2-area-sectorwe-i

 

ii)
the area Jamie will paint yellow. ai-sl-3-1-2-area-sectorweii


  • 1. Number & Algebra
    • 1.1 Number Toolkit
      • 1.1.1 Standard Form
        • 1.1.2 Exponents & Logarithms
          • 1.1.3 Approximation & Estimation
            • 1.1.4 GDC: Solving Equations
            • 1.2 Sequences & Series
              • 1.2.1 Language of Sequences & Series
                • 1.2.2 Arithmetic Sequences & Series
                  • 1.2.3 Geometric Sequences & Series
                    • 1.2.4 Applications of Sequences & Series
                    • 1.3 Financial Applications
                      • 1.3.1 Compound Interest & Depreciation
                        • 1.3.2 Amortisation & Annuities
                      • 2. Functions
                        • 2.1 Linear Functions & Graphs
                          • 2.1.1 Equations of a Straight Line
                          • 2.2 Further Functions & Graphs
                            • 2.2.1 Functions
                              • 2.2.2 Graphing Functions
                                • 2.2.3 Properties of Graphs
                                • 2.3 Modelling with Functions
                                  • 2.3.1 Linear & Piecewise Models
                                    • 2.3.2 Quadratic & Cubic Models
                                      • 2.3.3 Exponential Models
                                        • 2.3.4 Direct & Inverse Variation
                                          • 2.3.5 Sinusoidal Models
                                            • 2.3.6 Strategy for Modelling Functions
                                          • 3. Geometry & Trigonometry
                                            • 3.1 Geometry Toolkit
                                              • 3.1.1 Coordinate Geometry
                                                • 3.1.2 Arcs & Sectors
                                                • 3.2 Geometry of 3D Shapes
                                                  • 3.2.1 3D Coordinate Geometry
                                                    • 3.2.2 Volume & Surface Area
                                                    • 3.3 Trigonometry
                                                      • 3.3.1 Pythagoras & Right-Angled Triganometry
                                                        • 3.3.2 Non Right-Angled Trigonometry
                                                          • 3.3.3 Applications of Trigonometry & Pythagoras
                                                          • 3.4 Voronoi Diagrams
                                                            • 3.4.1 Voronoi Diagrams
                                                              • 3.4.2 Toxic Waste Dump Problem
                                                            • 4. Statistics & Probability
                                                              • 4.1 Statistics Toolkit
                                                                • 4.1.1 Sampling & Data Collection
                                                                  • 4.1.2 Statistical Measures
                                                                    • 4.1.3 Frequency Tables
                                                                      • 4.1.4 Linear Transformations of Data
                                                                        • 4.1.5 Outliers
                                                                          • 4.1.6 Univariate Data
                                                                            • 4.1.7 Interpreting Data
                                                                            • 4.2 Correlation & Regression
                                                                              • 4.2.1 Bivariate data
                                                                                • 4.2.2 Correlation Coefficients
                                                                                  • 4.2.3 Linear Regression
                                                                                  • 4.3 Probability
                                                                                    • 4.3.1 Probability & Types of Events
                                                                                      • 4.3.2 Conditional Probability
                                                                                        • 4.3.3 Sample Space Diagrams
                                                                                        • 4.4 Probability Distributions
                                                                                          • 4.4.1 Discrete Probability Distributions
                                                                                            • 4.4.2 Expected Values
                                                                                            • 4.5 Binomial Distribution
                                                                                              • 4.5.1 The Binomial Distribution
                                                                                                • 4.5.2 Calculating Binomial Probabilities
                                                                                                • 4.6 Normal Distribution
                                                                                                  • 4.6.1 The Normal Distribution
                                                                                                    • 4.6.2 Calculations with Normal Distribution
                                                                                                    • 4.7 Hypothesis Testing
                                                                                                      • 4.7.1 Hypothesis Testing
                                                                                                        • 4.7.2 Chi-squared Test for Independence
                                                                                                          • 4.7.3 Goodness of Fit Test
                                                                                                            • 4.7.4 The t-test
                                                                                                          • 5. Calculus
                                                                                                            • 5.1 Differentiation
                                                                                                              • 5.1.1 Introduction to Differentiation
                                                                                                                • 5.1.2 Applications of Differentiation
                                                                                                                  • 5.1.3 Modelling with Differentiation
                                                                                                                  • 5.2 Integration
                                                                                                                    • 5.2.1 Trapezoid Rule: Numerical Integration
                                                                                                                      • 5.2.2 Introduction to Integration
                                                                                                                        • 5.2.3 Applications of Integration


                                                                                                                        DOWNLOAD PDF

                                                                                                                      Author: Amber

                                                                                                                      Amber gained a first class degree in Mathematics & Meteorology from the University of Reading before training to become a teacher. She is passionate about teaching, having spent 8 years teaching GCSE and A Level Mathematics both in the UK and internationally. Amber loves creating bright and informative resources to help students reach their potential.


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