Autorentext

Paul La Rondie, Jill Stevens, Natasha Awada, Jennifer Chang Wathall, Ellen Thompson, Laurie Buchanan, Ed Kemp

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: analysis and approaches SL syllabus, for first teaching in September 2019.

Inhalt

• 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