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IB DP Maths: AI SL

Revision Notes

Home / DP / Maths: AI SL / IB / Revision Notes / 1. Number & Algebra / 1.1 Number Toolkit / 1.1.1 Standard Form


1.1.1 Standard Form


Standard form (sometimes called scientific notation or standard index form) gives us a way of writing very big and very small numbers using powers of 10.

Standard Form

Why use standard form?

  • Some numbers are too big or too small to write easily or for your calculator to display at all
    • Imagine the number 5050 , the answer would take 84 digits to write out
    • Try typing 5050 into your calculator, you will see it displayed in standard form
  • Writing very big or very small numbers in standard form allows us to:
    • Write them more neatly
    • Compare them more easily
    • Carry out calculations more easily
  • Exam questions could ask for your answer to be written in standard form

 

How is standard form written?

  • In standard form numbers are always written in the form a cross times 10 to the power of k where a and k satisfy the following conditions:
    • 1 space less or equal than a less than 10
      • So there is one non – zero digit before the decimal point
    • k space element of straight integer numbers 
      • So k must be an integer
    • k greater than 0 for large numbers
      • How many times a is multiplied by 10
    • k less than 0 for small numbers
      • How many times a is divided by 10

 

How are calculations carried out with standard form? 

  • Your GDC will display large and small numbers in standard form when it is in normal mode
    • Your GDC may display standard form as aEn
      • For example, 2.1 space cross times space 10 to the power of negative 5 end exponent will be displayed as 2.1 straight E minus 5
      • If so, be careful to rewrite the answer given in the correct form, you will not get marks for copying directly from your GDC
  • Your GDC will be able to carry out calculations in standard form
    • If you put your GDC into scientific mode it will automatically convert numbers into standard form
      • Beware that your GDC may have more than one mode when in scientific mode
      • This relates to the number of significant figures the answer will be displayed in
      • Your GDC may add extra zeros to fill spaces if working with a high number of significant figures, you do not need to write these in your answer
  • To add or subtract numbers written in the form a space cross times space 10 to the power of k without your GDC you will need to write them in full form first
  • To multiply or divide numbers written in the form a space cross times space 10 to the power of k without your GDC you can either write them in full form first or use the laws of indices

Worked Example

Calculate the following, giving your answer in the form a cross times 10 to the power of k, where 1 less or equal than a less than 10 space and k element of straight integer numbers.

 

i)
3780 space cross times space 200ai-sl-1-1-1-we-1-standard-form-part-i

 

 ii)   left parenthesis 7 space cross times space 10 to the power of 5 right parenthesis space minus space left parenthesis 5 space cross times space 10 to the power of 4 right parenthesis

ai-sl-1-1-1-we-1-standard-form-part-ii

 

iii)
left parenthesis 3.6 cross times 10 to the power of negative 3 end exponent right parenthesis left parenthesis 1.1 cross times 10 to the power of negative 8 end exponent right parenthesisai-sl-1-1-1-we-1-standard-form-part-iii



  • 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


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                                                                                                                      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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