Paul La Rondie, Jill Stevens, Natasha Awada, Jennifer Chang Wathall, Ellen Thompson, Laurie Buchanan, Ed Kemp
Oxford IB Diploma Programme: IB Mathematics: analysis and approaches
Paul La Rondie, Jill Stevens, Natasha Awada, Jennifer Chang Wathall, Ellen Thompson, Laurie Buchanan, Ed Kemp
Oxford IB Diploma Programme: IB Mathematics: analysis and approaches
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Featuring a wealth of digital content, this concept-based Print and Enhanced Online Course Book Pack has been developed in cooperation with the IB to provide the most comprehensive support for the new DP Mathematics: analysis and approaches SL syllabus, for first teaching in September 2019.
Featuring a wealth of digital content, this concept-based Print and Enhanced Online Course Book Pack has been developed in cooperation with the IB to provide the most comprehensive support for the new DP Mathematics: analysis and approaches SL syllabus, for first teaching in September 2019.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Oxford Children's Books
- Erscheinungstermin: 21. Februar 2019
- Englisch
- Abmessung: 258mm x 200mm x 30mm
- Gewicht: 1517g
- ISBN-13: 9780198427100
- ISBN-10: 0198427107
- Artikelnr.: 55581083
- Herstellerkennzeichnung
- Books on Demand GmbH
- In de Tarpen 42
- 22848 Norderstedt
- info@bod.de
- 040 53433511
- Verlag: Oxford Children's Books
- Erscheinungstermin: 21. Februar 2019
- Englisch
- Abmessung: 258mm x 200mm x 30mm
- Gewicht: 1517g
- ISBN-13: 9780198427100
- ISBN-10: 0198427107
- Artikelnr.: 55581083
- Herstellerkennzeichnung
- Books on Demand GmbH
- In de Tarpen 42
- 22848 Norderstedt
- info@bod.de
- 040 53433511
Paul La Rondie, Jill Stevens, Natasha Awada, Jennifer Chang Wathall, Ellen Thompson, Laurie Buchanan, Ed Kemp
* From patterns to generalizations: sequences and series
* 1.1: Number patterns and sigma notation
* 1.2: Arithmetic and geometric sequences
* 1.3: Arithmetic and geometric series
* 1.4: Modelling using arithmetic and geometric series
* 1.5: The binomial theorem
* 1.6: Proofs
* Representing relationships: introducing functions
* 2.1: What is a function?
* 2.2: Functional notation
* 2.3: Drawing graphs of functions
* 2.4: The domain and range of a function
* 2.5: Composition of functions
* 2.6: Inverse functions
* Modelling relationships: linear and quadratic functions
* 3.1: Parameters of a linear function
* 3.2: Linear functions
* 3.3: Transformations of functions
* 3.4: Graphing quadratic functions
* 3.5: Solving quadratic equations by factorization and completing the
square
* 3.6: The quadratic formula and the discriminant
* 3.7: Applications of quadratics
* Equivalent representations: rational functions
* 4.1: The reciprocal function
* 4.2: Transforming the reciprocal function
* 4.3: Rational functions of the form ax+b/cx+d
* Measuring change: differentiation
* 5.1: Limits and convergence
* 5.2: The derivative function
* 5.3: Differentiation rules
* 5.4: Graphical interpretation of first and second derivatives
* 5.5: Application of differential calculus: optimization and
kinematics
* Representing data: statistics for univariate data
* 6.1: Sampling
* 6.2: Presentation of data
* 6.3: Measures of central tendency
* 6.4: Measures of dispersion
* Modelling relationships between two data sets: statistics for
bivariate data
* 7.1: Scatter diagrams
* 7.2: Measuring correlation
* 7.3: The line of best fit
* 7.4: Least squares regression
* Quantifying randomness: probability
* 8.1: Theoretical and experimental probability
* 8.2: Representing probabilities: Venn diagrams and sample spaces
* 8.3: Independent and dependent events and conditional probability
* 8.4: Probability tree diagrams
* Representing equivalent quantities: exponentials and logarithms
* 9.1: Exponents
* 9.2: Logarithms
* 9.3: Derivatives of exponential functions and the natural logarithmic
function
* From approximation to generalization: integration
* 10.1: Antiderivatives and the indefinite integral
* 10.2: More on indefinite integrals
* 10.3: Area and definite integrals
* 10.4: Fundamental theorem of calculus
* 10.5: Area between two curves
* Relationships in space: geometry and trigonometry in 2D and 3D
* 11.1: The geometry of 3D shapes
* 11.1: Right-angles triangle trigonometry
* 11.3: The sine rule
* 11.4: The cosine rule
* 11.5: Applications of right and non-right angled trigonometry
* Periodic relationships: trigonometric functions
* 12.1: Radian measure, arcs, sectors and segments
* 12.2: Trigonometric ratios in the unit circle
* 12.3: Trigonometric identities and equations
* 12.4: Trigonometric functions
* Modelling change: more calculus
* 13.1: Derivatives with sine and cosine
* 13.2: Applications of derivatives
* 13,3: Integration with sine, cosine and substitution
* 13.4: Kinematics and accumulating change
* Valid comparisons and informed decisions: probability distributions
* 14.1: Random variables
* 14.2: The binomial distribution
* 14.3: The normal distribution
* Exploration
* 1.1: Number patterns and sigma notation
* 1.2: Arithmetic and geometric sequences
* 1.3: Arithmetic and geometric series
* 1.4: Modelling using arithmetic and geometric series
* 1.5: The binomial theorem
* 1.6: Proofs
* Representing relationships: introducing functions
* 2.1: What is a function?
* 2.2: Functional notation
* 2.3: Drawing graphs of functions
* 2.4: The domain and range of a function
* 2.5: Composition of functions
* 2.6: Inverse functions
* Modelling relationships: linear and quadratic functions
* 3.1: Parameters of a linear function
* 3.2: Linear functions
* 3.3: Transformations of functions
* 3.4: Graphing quadratic functions
* 3.5: Solving quadratic equations by factorization and completing the
square
* 3.6: The quadratic formula and the discriminant
* 3.7: Applications of quadratics
* Equivalent representations: rational functions
* 4.1: The reciprocal function
* 4.2: Transforming the reciprocal function
* 4.3: Rational functions of the form ax+b/cx+d
* Measuring change: differentiation
* 5.1: Limits and convergence
* 5.2: The derivative function
* 5.3: Differentiation rules
* 5.4: Graphical interpretation of first and second derivatives
* 5.5: Application of differential calculus: optimization and
kinematics
* Representing data: statistics for univariate data
* 6.1: Sampling
* 6.2: Presentation of data
* 6.3: Measures of central tendency
* 6.4: Measures of dispersion
* Modelling relationships between two data sets: statistics for
bivariate data
* 7.1: Scatter diagrams
* 7.2: Measuring correlation
* 7.3: The line of best fit
* 7.4: Least squares regression
* Quantifying randomness: probability
* 8.1: Theoretical and experimental probability
* 8.2: Representing probabilities: Venn diagrams and sample spaces
* 8.3: Independent and dependent events and conditional probability
* 8.4: Probability tree diagrams
* Representing equivalent quantities: exponentials and logarithms
* 9.1: Exponents
* 9.2: Logarithms
* 9.3: Derivatives of exponential functions and the natural logarithmic
function
* From approximation to generalization: integration
* 10.1: Antiderivatives and the indefinite integral
* 10.2: More on indefinite integrals
* 10.3: Area and definite integrals
* 10.4: Fundamental theorem of calculus
* 10.5: Area between two curves
* Relationships in space: geometry and trigonometry in 2D and 3D
* 11.1: The geometry of 3D shapes
* 11.1: Right-angles triangle trigonometry
* 11.3: The sine rule
* 11.4: The cosine rule
* 11.5: Applications of right and non-right angled trigonometry
* Periodic relationships: trigonometric functions
* 12.1: Radian measure, arcs, sectors and segments
* 12.2: Trigonometric ratios in the unit circle
* 12.3: Trigonometric identities and equations
* 12.4: Trigonometric functions
* Modelling change: more calculus
* 13.1: Derivatives with sine and cosine
* 13.2: Applications of derivatives
* 13,3: Integration with sine, cosine and substitution
* 13.4: Kinematics and accumulating change
* Valid comparisons and informed decisions: probability distributions
* 14.1: Random variables
* 14.2: The binomial distribution
* 14.3: The normal distribution
* Exploration
* From patterns to generalizations: sequences and series
* 1.1: Number patterns and sigma notation
* 1.2: Arithmetic and geometric sequences
* 1.3: Arithmetic and geometric series
* 1.4: Modelling using arithmetic and geometric series
* 1.5: The binomial theorem
* 1.6: Proofs
* Representing relationships: introducing functions
* 2.1: What is a function?
* 2.2: Functional notation
* 2.3: Drawing graphs of functions
* 2.4: The domain and range of a function
* 2.5: Composition of functions
* 2.6: Inverse functions
* Modelling relationships: linear and quadratic functions
* 3.1: Parameters of a linear function
* 3.2: Linear functions
* 3.3: Transformations of functions
* 3.4: Graphing quadratic functions
* 3.5: Solving quadratic equations by factorization and completing the
square
* 3.6: The quadratic formula and the discriminant
* 3.7: Applications of quadratics
* Equivalent representations: rational functions
* 4.1: The reciprocal function
* 4.2: Transforming the reciprocal function
* 4.3: Rational functions of the form ax+b/cx+d
* Measuring change: differentiation
* 5.1: Limits and convergence
* 5.2: The derivative function
* 5.3: Differentiation rules
* 5.4: Graphical interpretation of first and second derivatives
* 5.5: Application of differential calculus: optimization and
kinematics
* Representing data: statistics for univariate data
* 6.1: Sampling
* 6.2: Presentation of data
* 6.3: Measures of central tendency
* 6.4: Measures of dispersion
* Modelling relationships between two data sets: statistics for
bivariate data
* 7.1: Scatter diagrams
* 7.2: Measuring correlation
* 7.3: The line of best fit
* 7.4: Least squares regression
* Quantifying randomness: probability
* 8.1: Theoretical and experimental probability
* 8.2: Representing probabilities: Venn diagrams and sample spaces
* 8.3: Independent and dependent events and conditional probability
* 8.4: Probability tree diagrams
* Representing equivalent quantities: exponentials and logarithms
* 9.1: Exponents
* 9.2: Logarithms
* 9.3: Derivatives of exponential functions and the natural logarithmic
function
* From approximation to generalization: integration
* 10.1: Antiderivatives and the indefinite integral
* 10.2: More on indefinite integrals
* 10.3: Area and definite integrals
* 10.4: Fundamental theorem of calculus
* 10.5: Area between two curves
* Relationships in space: geometry and trigonometry in 2D and 3D
* 11.1: The geometry of 3D shapes
* 11.1: Right-angles triangle trigonometry
* 11.3: The sine rule
* 11.4: The cosine rule
* 11.5: Applications of right and non-right angled trigonometry
* Periodic relationships: trigonometric functions
* 12.1: Radian measure, arcs, sectors and segments
* 12.2: Trigonometric ratios in the unit circle
* 12.3: Trigonometric identities and equations
* 12.4: Trigonometric functions
* Modelling change: more calculus
* 13.1: Derivatives with sine and cosine
* 13.2: Applications of derivatives
* 13,3: Integration with sine, cosine and substitution
* 13.4: Kinematics and accumulating change
* Valid comparisons and informed decisions: probability distributions
* 14.1: Random variables
* 14.2: The binomial distribution
* 14.3: The normal distribution
* Exploration
* 1.1: Number patterns and sigma notation
* 1.2: Arithmetic and geometric sequences
* 1.3: Arithmetic and geometric series
* 1.4: Modelling using arithmetic and geometric series
* 1.5: The binomial theorem
* 1.6: Proofs
* Representing relationships: introducing functions
* 2.1: What is a function?
* 2.2: Functional notation
* 2.3: Drawing graphs of functions
* 2.4: The domain and range of a function
* 2.5: Composition of functions
* 2.6: Inverse functions
* Modelling relationships: linear and quadratic functions
* 3.1: Parameters of a linear function
* 3.2: Linear functions
* 3.3: Transformations of functions
* 3.4: Graphing quadratic functions
* 3.5: Solving quadratic equations by factorization and completing the
square
* 3.6: The quadratic formula and the discriminant
* 3.7: Applications of quadratics
* Equivalent representations: rational functions
* 4.1: The reciprocal function
* 4.2: Transforming the reciprocal function
* 4.3: Rational functions of the form ax+b/cx+d
* Measuring change: differentiation
* 5.1: Limits and convergence
* 5.2: The derivative function
* 5.3: Differentiation rules
* 5.4: Graphical interpretation of first and second derivatives
* 5.5: Application of differential calculus: optimization and
kinematics
* Representing data: statistics for univariate data
* 6.1: Sampling
* 6.2: Presentation of data
* 6.3: Measures of central tendency
* 6.4: Measures of dispersion
* Modelling relationships between two data sets: statistics for
bivariate data
* 7.1: Scatter diagrams
* 7.2: Measuring correlation
* 7.3: The line of best fit
* 7.4: Least squares regression
* Quantifying randomness: probability
* 8.1: Theoretical and experimental probability
* 8.2: Representing probabilities: Venn diagrams and sample spaces
* 8.3: Independent and dependent events and conditional probability
* 8.4: Probability tree diagrams
* Representing equivalent quantities: exponentials and logarithms
* 9.1: Exponents
* 9.2: Logarithms
* 9.3: Derivatives of exponential functions and the natural logarithmic
function
* From approximation to generalization: integration
* 10.1: Antiderivatives and the indefinite integral
* 10.2: More on indefinite integrals
* 10.3: Area and definite integrals
* 10.4: Fundamental theorem of calculus
* 10.5: Area between two curves
* Relationships in space: geometry and trigonometry in 2D and 3D
* 11.1: The geometry of 3D shapes
* 11.1: Right-angles triangle trigonometry
* 11.3: The sine rule
* 11.4: The cosine rule
* 11.5: Applications of right and non-right angled trigonometry
* Periodic relationships: trigonometric functions
* 12.1: Radian measure, arcs, sectors and segments
* 12.2: Trigonometric ratios in the unit circle
* 12.3: Trigonometric identities and equations
* 12.4: Trigonometric functions
* Modelling change: more calculus
* 13.1: Derivatives with sine and cosine
* 13.2: Applications of derivatives
* 13,3: Integration with sine, cosine and substitution
* 13.4: Kinematics and accumulating change
* Valid comparisons and informed decisions: probability distributions
* 14.1: Random variables
* 14.2: The binomial distribution
* 14.3: The normal distribution
* Exploration