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