Topic 1: Number and algebra
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1.1 Scientific notation (10:44)
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1.2.1 Arithmetic sequences and series (12:13)
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1.2.2 Sigma notation (5:05)
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1.3 Geometric sequences and series (13:52)
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1.4.1 Compound interest (11:51)
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1.4.2 Depreciation (6:21)
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1.4.3 Inflation (5:28)
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1.5.1 Laws of exponents (4:04)
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1.5.2 Introduction to logs (10:43)
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1.5.3 The number e (10:25)
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1.6.1 Rounding (10:05)
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1.6.2 Upper and lower bounds (8:09)
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1.6.3 Percentage error (5:51)
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1.7.1 Loans (8:35)
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1.7.2 Annuities (10:16)
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1.8.1 System of linear equations (3:17)
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1.8.2 Roots of a polynomial (6:03)
Topic 2: Functions
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2.1.1 Gradient of a line (8:34)
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2.1.2 Equation of a straight line (5:58)
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2.1.3 Parallel and perpendicular lines (8:25)
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2.2.1 Functions introduction (13:26)
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2.2.2 Evaluating functions (6:08)
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2.2.3 Inverse functions (11:21)
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2.3 Sketching functions (9:07)
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2.4.1 Features of graphs (12:22)
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2.4.2 Asymptotes (9:01)
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2.5.1 Linear modelling (10:39)
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2.5.2 Quadratic functions (6:34)
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2.5.3 Quadratic modelling (10:14)
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2.5.4 Exponential modelling (14:33)
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2.5.5 Direct and inverse variation (14:55)
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2.5.6 Cubic modelling (11:29)
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2.5.7 Sinusoidal graphs (13:13)
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2.5.8 Creating a sinusoidal model (8:56)
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2.6 Finding the parameters of a model (6:22)
Topic 3: Geometry and trigonometry
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3.1.1 Midpoint of a line segment (4:54)
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3.1.2 Distance between 2 points (5:37)
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3.1.3 Volume and surface area (14:44)
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3.1.4 Trigonometry in 3d (15:12)
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3.2.1 Pythagoras' theorem (3:00)
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3.2.2 Soh cah toa (8:21)
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3.2.3 Sine rule (6:16)
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3.2.4 Cosine rule (6:59)
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3.2.5 Area of a triangle (2:58)
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3.3.1 Bearings (10:46)
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3.3.2 Angles of elevation and depression (8:22)
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3.4 Arcs and Sectors (5:10)
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3.5 Perpendicular bisectors (15:59)
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3.6.1 Voronoi diagrams intro (11:09)
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3.6.2 Voronoi examples (14:53)
Topic 4: Statistics and probability
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4.1.1 Discrete v continuous data (7:28)
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4.1.2 Sampling techniques (10:44)
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4.2.1 Histograms and cumulative frequency curves (21:04)
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4.2.2 Box and whisker diagrams (6:37)
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4.2.3 Interpreting box plots (8:23)
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4.2.4 Outliers (9:30)
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4.3.1 Averages and spread (11:22)
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4.3.2 Frequency tables (14:10)
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4.3.3 Constant changes to data (8:42)
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4.3.4 Variance and standard deviation by hand (8:12)
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4.4 Linear regression and correlation (21:52)
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4.5 Probability formulae (9:47)
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4.6.1 Venn diagrams (19:15)
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4.6.2 Tree Diagrams (13:29)
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4.7 Discrete random variables (13:41)
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4.8 Binomial distribution (17:18)
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4.9 Normal distribution (28:45)
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4.10 Spearman's rank correlation coefficient (17:09)
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4.11.1 Chi Squared intro (10:34)
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4.11.2 Chi Squared test for independence (16:57)
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4.11.3 Chi squared goodness of fit (11:45)
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4.11.4 T-test (19:21)
Topic 5: Calculus
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5.1.1 Introduction to differentiation (13:20)
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5.1.2 Introduction to limits (16:17)
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5.2 Increasing and decreasing functions (12:49)
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5.3.1 Differentiation power rule (9:37)
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5.3.2 Derivative at a point (6:03)
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5.4 Tangents and normals (9:49)
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5.5.1 Integration (power rule) (11:50)
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5.5.2 Finding f(x) (5:24)
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5.5.3 Area under the curve (9:03)
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5.6 Stationary points (11:27)
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5.7 Optimization (16:10)
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5.8 Trapezoidal rule (14:16)
Internal assessment
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1. IA Introduction (10:22)
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2.1 A Presentation (12:45)
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2.2 B Mathematical communication (9:25)
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2.3 C Personal engagement (11:04)
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2.4 D Reflection (5:34)
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2.5 E Use of mathematics (8:42)
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3.1 Choosing a topic 1 (17:52)
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3.2 Choosing a topic 2 (19:57)
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4.1 Quadratic from basketball video (8:04)
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4.1.2 Basketball analysis (11:26)
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4.2 Quadratic fit on photo (13:57)
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4.3 Sinusoidal fit on photo (4:33)
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4.4 Data modelling with Excel (7:41)
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4.5 Data modelling with Geogebra (10:34)
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5 Marking an IA (20:14)
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6.1 Ideas part 1 - Modelling (18:20)
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6.2 Ideas part 2 (18:36)
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6.3 Ideas part 3 (14:44)
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Sample Volume of Revolution Glasses (3:47)
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Sample Swimming IA Normal Distribution (3:58)
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Sample Angry Birds Equation of a Tangent (3:58)
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Sample Gini Coefficient Integration (4:58)
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Sample Optimum Long Jump Distance Calculus (5:34)
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Sample Table Tennis Shot Comparison (5:19)
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Sample Volume of Revoltion HL (3:55)
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Sample Linear Correlation Time v Calories (5:25)
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Sample Surface Area of a Chocolate Egg (2:48)
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Sample Ibuprofen v Paracetamol Calculus (3:46)
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Sample Polynomial Modelling Caffeine v Performance (5:05)
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Sample India v China Population Modelling (5:09)
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Sample Area of a School Integration (2:48)
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Sample Modelling the Dubai Eye Trig Modelling (4:05)
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Sample Volleyball Serve (6:32)
Specimen paper 1
Specimen paper 2
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Question 1 a (6:16)
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Question 1 b c (10:08)
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Question 1 d (5:08)
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Question 2 a b (6:41)
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Question 2 c d (5:14)
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Question 2 e f g (6:08)
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Question 3 a b (7:39)
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Question 3 c (3:18)
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Question 3 d e f (9:47)
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Question 4 a b (7:42)
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Question 4 c d (7:33)
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Question 4 e (7:15)
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Question 5 a (6:43)
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Question 5 b c d (9:52)
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Question 5 e f (5:27)
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Question 5 g (7:51)
May 2021 TZ1 P1
May 2021 TZ1 P2
2021 May TZ2 P1
2021 May TZ2 P2
2021 November P1
2021 November P2
2022 May TZ1 P1
2022 May TZ1 P2
2022 May TZ2 P1
2022 May tz2 p2
2022 November Paper 1
2022 November Paper 2
2023 May TZ1 P1
2023 May TZ1 P2
2023 May TZ2 P1
2023 May TZ2 P2
2023 November P1
2023 November P2
