Autorentext

Jane Forrest, Paula Waldman, Jennifer Chang Wathall, Suzanne Doering, David Harris, Nadia Stoyanova Kennedy

Klappentext

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 SL syllabus, for first teaching in September 2019.

Inhalt

• Measuring space: accuracy and 2D geometry
• 1.1: Measurements and estimates
• 1.2: Recording measurements, significant digits and rounding
• 1.3: Measurements: exact or approximate?
• 1.4: Speaking scientifically
• 1.5: Trigonometry of right-angled triangles and indirect measurements
• 1.6: Angles of elevation and depression
• Representing space: non-right angled trigonometry and volumes
• 2.1: Trigonometry of non-right triangles
• 2.2: Area of triangle formula. Applications of right and non-right angled trigonometry
• 2.3: Geometry: solids, surface area and volume
• Representing and describing data: descriptive statistics
• 3.1: Collecting and organising univariate data
• 3.2: Sampling techniques
• 3.3: Presentation of data
• 3.4: Bivariate data
• Dividing up space: coordinate geometry, lines, Voronoi diagrams
• 4.1: Coordinates, distance and midpoint formula in 2D and 3D
• 4.2: Gradient of lines and its applications
• 4.3: Equations of straight lines; different forms of equations
• 4.4: Parallel and perpendicular lines
• 4.5: Voronoi diagrams and toxic waste problem
• Modelling constant rates of change: linear functions
• 5.1: Functions
• 5.2: Linear Models
• 5.3: Arithmetic Sequences
• 5.4: Modelling
• Modelling relationships: linear correlation of bivariate data
• 6.1: Measuring correlation
• 6.2: The line of best fit
• 6.3: Interpreting the regression line
• Quantifying uncertainty: probability, binomial and normal distributions
• 7.1: Theoretical and experimental probability
• 7.2: Representing combined probabilities with diagrams
• 7.3: Representing combined probabilities with diagrams and formulae
• 7.4: Complete, concise and consistent representations
• 7.5: Modelling random behaviour: random variables and probability distributions
• 7.6: Modelling the number of successes in a fixed number of trials
• 7.7: Modelling measurements that are distributed randomly
• Testing for validity: Spearman's, hypothesis testing and x^2 test for independence
• 8.1: Spearman's rank correlation coefficient
• 8.2: chi^2 test for independence
• 8.3: chi^2 goodness of fit test
• 8.4: The t-test
• Modelling relationships with functions: power functions
• 9.1: Quadratic models
• 9.2: Problems involving quadratics
• 9.3: Cubic models, power functions and direct and inverse variation
• 9.4: Optimisation
• Modelling rates of change: exponential and logarithmic functions
• 10.1: Geometric sequences and series
• 10.2: Compound interest, annuities, amortization
• 10.3: Exponential models
• 10.4: Exponential equations and logarithms
• Modelling periodic phenomena: trigonometric functions
• 11.1: An introduction to periodic functions
• 11.2: An infinity of sinusoidal functions
• 11.3: A world of sinusoidal models
• Analyzing rates of change: differential calculus
• 12.1: Limits and derivatives
• 12.2: Equation of tangent and normal and increasing and decreasing functions
• 12.3: Maximum and minimum points and optimisation
• Approximating irregular spaces: integration
• 13.1: Finding areas
• 13.2: Integration: the reverse processes of differentiation
• Exploration