Tony Halsey, Suzanne Doering, Michael Ortman, Nuriye Sirinoglu Singh, Peter Gray, David Harris, Jennifer Chang Wathall

Oxford IB Diploma Programme: IB Mathematics: applications and interpretation, Higher Level, Print and Enhanced Online Course Book Pack

• Broschiertes Buch

Produktbeschreibung

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: applications and interpretation HL syllabus, for first teaching in September 2019.

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Produktdetails

• Verlag: Oxford Children's Books
• Seitenzahl: 832
• Erscheinungstermin: 21. März 2019
• Englisch
• Abmessung: 256mm x 197mm x 44mm
• Gewicht: 1766g
• ISBN-13: 9780198427049
• ISBN-10: 0198427042
• Artikelnr.: 55910836

Autorenporträt

Panayiotis Economopoulos, Tony Halsey, Suzanne Doering, Michael Ortman, Nuriye Sirinoglu Singh, Peter Gray, David Harris, Jennifer Chang Wathall

Inhaltsangabe

* Measuring space: accuracy and geometry
* 1.1: Representing numbers exactly and approximately
* 1.2: Angles and triangles
* 1.3: three-dimensional geometry
* Representing and describing data: descriptive statistics
* 2.1: Collecting and organizing data
* 2.2: Statistical measures
* 2.3: Ways in which we can present data
* 2.4: Bivariate data
* Dividing up space: coordinate geometry, lines, Voronoi diagrams,
vectors
* 3.1: Coordinate geometry in 2 and 3 dimensions
* 3.2: The equation of a straight line in 2 dimensions
* 3.3: Voronoi diagrams
* 3.4: Displacement vectors
* 3.5: The scalar and vector product
* 3.6: Vector equations of lines
* Modelling constant rates of change: linear functions and regressions
* 4.1: Functions
* 4.2: Linear models
* 4.3: Inverse functions
* 4.4: Arithmetic sequences and series
* 4.5: Linear regression
* Quantifying uncertainty: probability
* 5.1: Theoretical and experimental probability
* 5.2: Representing combined probabilities with diagrams
* 5.3: Representing combined probabilities with diagrams and formulae
* 5.4: Complete, concise and consistent representations
* Modelling relationships with functions: power and polynomial
functions
* 6.1: Quadratic models
* 6.2: Quadratic modelling
* 6.3: Cubic functions and models
* 6.4: Power functions, inverse variation and models
* Modelling rates of change: exponential and logarithmic functions
* 7.1: Geometric sequences and series
* 7.2: Financial applications of geometric sequences and series
* 7.3: Exponential functions and models
* 7.4: Laws of exponents - laws of logarithms
* 7.5: Logistic models
* Modelling periodic phenomena: trigonometric functions and complex
numbers
* 8.1: Measuring angles
* 8.2: Sinusoidal models: f(x) = asin(b(x-c))+d
* 8.3: Completing our number system
* 8.4: A geometrical interpretation of complex numbers
* 8.5: Using complex numbers to understand periodic models
* Modelling with matrices: storing and analyzing data
* 9.1: Introduction to matrices and matrix operations
* 9.2: Matrix multiplication and properties
* 9.3: Solving systems of equations using matrices
* 9.4: Transformations of the plane
* 9.5: Representing systems
* 9.6: Representing steady state systems
* 9.7: Eigenvalues and eigenvectors
* Analyzing rates of change: differential calculus
* 10.1: Limits and derivatives
* 10.2: Differentiation: further rules and techniques
* 10.3: Applications and higher derivatives
* Approximating irregular spaces: integration and differential
equations
* 11.1: Finding approximate areas for irregular regions
* 11.2: Indefinite integrals and techniques of integration
* 11.3: Applications of integration
* 11.4: Differential equations
* 11.5: Slope fields and differential equations
* Modelling motion and change in 2D and 3D: vectors and differential
equations
* 12.1: Vector quantities
* 12.2: Motion with variable velocity
* 12.3: Exact solutions of coupled differential equations
* 12.4: Approximate solutions to coupled linear equations
* Representing multiple outcomes: random variables and probability
distributions
* 13.1: Modelling random behaviour
* 13.2: Modelling the number of successes in a fixed number of trials
* 13.3: Modelling the number of successes in a fixed interval
* 13.4: Modelling measurements that are distributed randomly
* 13.5: Mean and variance of transformed or combined random variables
* 13.6: Distributions of combined random variables
* Testing for validity: Spearman's hypothesis testing and x^2 test for
independence
* 14.1: Spearman's rank correlation coefficient
* 14.2: Hypothesis testing for the binomial probability, the Poisson
mean and the product moment correlation coefficient
* 14.3: Testing for the mean of a normal distribution
* 14.4: Chi-squared test for independence
* 14.5: Chi-squared goodness-of-fit test
* 14.6: Choice, validity and interpretation of tests
* Optimizing complex networks: graph theory
* 15.1: Constructing graphs
* 15.2: Graph theory for unweighted graphs
* 15.3: Graph theory for weighted graphs: the minimum spanning tree
* 15.4: Graph theory for weighted graphs - the Chinese postman problem
* 15.5: Graph theory for weighted graphs - the travelling salesman
problem
* Exploration