Download presentation
1
Whiteboard Templates for Maths
HW Graph Paper Number… Algebra Statistical Charts Calculator Area & Volume Geometry… Trigonometry Probability Functions… Navigation Icons Parent Menu Home Page Last Viewed External Link Animation Levels MDT Resource Medium Grid 3 Draft Version 17.2 Created :
2
Medium Grid
3
Medium Grid with optional dividers
4
4
Graph Paper Divided Board Plan Graphing Functions Medium Grid
Large Grid Small Grid Split Screen Divided Board Plan Whiteboard 6 Frames 4 Frames Key Words How to… Steps Graphing Functions Prior Knowledge Given Couples Substitution Trigonometric Functions & Calculus
5
Large Grid 1
6
Small Grid
7
Very Small Grid with optional dividers
6
8
Split Screen Medium Grid
9
Whiteboard with optional dividers
4
10
6 Framed Sections
11
4 Framed Sections
12
Medium Grid with Key Words
Topic: Key Words
13
Medium Grid with Steps Steps How to…
14
Medium Grid with Prior Knowledge
15
Graphing a Function using a given Table
Function: Domain: 3
16
Evaluating Outputs and Graphing a Function
Function: Domain: 3
17
Trigonometric Functions
Sin(A) Cos(A)
18
Graphing a Sine Function
Function: Domain: sin(x) 1
19
Graphing a Cosine Function
Function: Domain: 1
20
Algebra Solving Equations Using Arrays Algebra Tiles Quadratic Roots
Linear Patterns Quadratic Pattern Binomial Theorem
21
Algebra Tiles 1 x x2 x -x2 -x -1 -x
22
Roots of a Quadratic Equation
Roots of the quadratic equation ax2 + bx + c = 0 p.20
23
The Binomial Theorem p.20
24
Solving Equations & Inequalities
Inequality Double inequality
25
Solving Equations 2
26
Solving Inequalities 1
27
Solving Double Inequalities
1
28
Growing Visual Linear Patterns
Supporting Student Workbook on Linear Patterns Available Online Click on the Pattern
29
Linear Patterns
30
How many dots are there?
31
How many dots are there?
32
How many dots are there?
33
How many dots are there?
34
IMAGINE A SQUARE WITH 10 DOTS AT EACH SIDE
How many dots are there? IMAGINE A SQUARE WITH 10 DOTS AT EACH SIDE
35
Pattern 1 1st Difference 3
36
Pattern 2 1st Difference 3
37
Pattern 3 1st Difference 3
38
Pattern 4 1st Difference 3
39
Pattern 5 1st Difference 3
40
Pattern 6 1st Difference 3
41
Pattern 7 1st Difference 3
42
Pattern 8 1st Difference 3
43
Pattern 9 1st Difference 3
44
Pattern 10 John wants to save up for a school tour which will happen at the end of the school year. He speaks to his parents about it and they agree that he can get a part-time job to help him afford the trip. His parents give him €100 to start him off and each week he saves €20 of his wages. 1st Difference 3
45
Quadratic Factors Trial & Error
Using Arrays Quadratic Array Two Quadratic Arrays Quadratic Factors Quadratic Factors Trial & Error Cubic Array Two Cubic Arrays
46
Quadratic Array for Multiplication and Division
Question: Answer:
47
Quadratic Arrays for Multiplication and Division
48
Quadratic Factorisation using the Guide Method
Question: Guide Number Product Factors Sum Answer:
49
Quadratic Factorisation using the Guide Method
Question: Guide Number Product Factors Sum Answer:
50
Cubic Array for Multiplication and Division
Question: Answer:
51
Cubic Arrays for Multiplication and Division
52
Growing Visual Quadratic Patterns
Supporting the Student Workbook on Quadratic Patterns available on our website Click on the pattern to go to that page. Pattern 5 Pattern 10 Pattern 1 Pattern 6 Pattern 11 Pattern 2 Pattern 7 Pattern 12 Pattern 3 Pattern 8 Pattern 13 Pattern 4 Pattern 9 Pattern 14
53
Quadtatic Pattern Next, Near, Far, Any? 4 Stage No. (n)
No. of squares (s) 1st Difference 2nd Difference 4
54
Pattern 1 1st Difference 2nd Difference 3
55
Pattern 2 1st Difference 2nd Difference 3
56
Pattern 3 1st Difference 2nd Difference 3
57
Pattern 4 1st Difference 2nd Difference 3
58
Pattern 5 1st Difference 2nd Difference 3
59
Pattern 6 1st Difference 2nd Difference 3
60
Pattern 7 1st Difference 2nd Difference 3
61
Pattern 8 1st Difference 2nd Difference 3
62
Pattern 9 1st Difference 2nd Difference 3
63
Pattern 10 1st Difference 2nd Difference 3
64
Pattern 11 1st Difference 2nd Difference 3
65
Pattern 12 1st Difference 2nd Difference 3
66
Pattern 13 1st Difference 2nd Difference 3
67
Pattern 14 A tiling company specialises in multi-colour tile patterns. A small guest house is interested in the pattern below for its square shaped reception area. How many tile will be needed in total if the reception area needs 36 green tiles in the centre pattern? 1st Difference 2nd Difference 3
68
Back-to-Back Stemplot
Statistical Charts Line Plot Bar Chart Histogram Pie Chart Stemplot Back-to-Back Stemplot Scatter Graph
69
Line Plot Title: 1
70
Bar Chart Title: 1
71
Histogram Title: 1
72
Stemplot Title: Key: 1
73
Back to Back Stemplot Title: Key: Key: 1
74
Scatter Graph Title: 1
75
Pie Chart Title: 1
76
Number Number Lines Fractions Order of Operations Venn Diagrams
Number Systems Complex No. Indices Logarithms Sequences… Financial Maths
77
Venn Diagrams 1 Set 2 Sets 3 Sets
78
Venn Diagram with 1 Set 1
79
Venn Diagram with 2 Sets 1
80
Venn Diagram with 3 Sets 1
81
Number Line 1 2 3 4 5 6 7 8 9 10 -9 -8 -7 -6 -5 -4 -3 -2 -1 -10 1 2 3 4 5 6 7 8 9 10 11 12 -9 -8 -7 -6 -5 -4 -3 -2 -1 -10 3
82
Using the Calculator
83
Complex Numbers Argand Diagrams Rectangular Form Polar Form
Number Systems De Moivre
84
Complex Numbers: Argand Diagram
Im Re
85
Argand Diagram: Complex Numbers in Polar Form
Im Re
86
Complex Numbers: De Moivre’s Theorem
87
Order of Operations BEMDAS BIMDAS BIRDMAS
88
Order of Operations - BEMDAS
left to right A S
89
Order of Operations - BIDMAS
M D left to right A S
90
Order of Operations - BIRDMAS
left to right A S
91
Inferential Statistics
Probability Empirical Rule Probability Tables Bernoulli Trials Inferential Statistics Ordinary Level Higher Level
92
The Empirical Rule for Normal Distribution
1
93
Normal Distribution Tables
standardising formula p.34 p.36-37
94
Bernoulli Trials p.33
95
Inferential Statistics
LC Ordinary Level – Sample Proportions Margin of Error Confidence Interval Hypothesis Test HL
96
Margin of Error of the Proportion (OL)
Ordinary Level Approximation for the 95% level of confidence margin of error: n Sample size This formula is not in Formulae and Tables. It is an approximation relating to the product of the 95% level of confidence z-value (p.37) and the standard error of the proportion (p.34)
97
95% Confidence Interval of the Proportion (OL)
Population proportion Sample proportion n Sample size This formula is not in Formulae and Tables.
98
Hypothesis Test on a Population Proportion (OL)
State the Hypotheses Analyse sample data Interpret the results Step 1 – State the Hypotheses State the null hypothesis (H0) and the alternative hypothesis (H1). p Population proportion p0 Hypothesised value of the population proportion H0 is a statement of no change. We express it as a statement of equality. Note: Stating the alternative hypothesis as “not being equal” means that it could be either “less than” or “greater than” a value. This results in a two-tailed hypothesis test.
99
Hypothesis Test on a Population Proportion (OL)
State the Hypothesis Analyse sample data Interpret the results Step 2 – Analyse the sample data using a confidence interval Construct the 95% confidence interval State if p0 is inside or outside the confidence interval Step 3 - Interpret the results If p0 is outside the interval it would indicate that p ≠ p0 so the result is significant and we reject H0. If p0 is inside the interval we fail to reject H0. Clearly state your conclusion.
100
Inferential Statistics
LC Higher Level Proportions Margin of Error Sample Size? Confidence Interval Hypothesis Tests Means CI for Population Mean CI for Sample Mean Hypothesis Tests OL
101
95% Margin of Error for a Population Proportion (HL)
Higher Level 95% level of confidence margin of error: p Population proportion Sample proportion n Sample size Standard error of the proportion (p.34) This formula is not given in Formulae and Tables is the z-value relating to a 95% level of confidence (p.37).
102
Sample Size for a required Margin of Error (HL)
Use the approximation for the 95% level of confidence margin of error for a Population Proportion: n Sample size Margin of error for 95% L.o.C This formula is not in Formulae and Tables. It is an approximation relating to the product of the 95% level of confidence z-value (p.37) and the standard error of the proportion (p.34)
103
95% Confidence Interval for a Population Proportion - HL
This formula is not in Formulae and Tables. It is a confidence interval based on the standard deviation of σ “p hat.” p Population proportion Sample proportion n Sample size Standard error of the proportion (p.34)
104
Hypothesis Test on a Population Proportion - HL
State the Hypotheses Analyse sample data Interpret the results Step 1 – State the Hypotheses State the null hypothesis (H0) and the alternative hypothesis (H1). p Population proportion p0 Hypothesised value of the population proportion H0 is a statement of no change. We express it as a statement of equality. Note: Stating the alternative hypothesis as “not being equal” means that it could be either “less than” or “greater than” a value. This results in a two-tailed hypothesis test.
105
Hypothesis Test on a Population Proportion - HL
State the Hypothesis Analyse sample data Interpret the results Step 2 Analyse the sample data using either a: Confidence interval Z-value P-value
106
Hypothesis Test on a Population Proportion - HL
State the Hypothesis Analyse sample data Interpret the results Step 2 – Analyse the sample data using a confidence interval Construct the required confidence interval for a proportion p.34 State if p0 is inside or outside the confidence interval Step 3 - Interpret the results If p0 is outside the interval it would indicate that p ≠ p0 so the result is significant and we reject H0. If p0 is inside the interval we fail to reject H0. Clearly state your conclusion.
107
Hypothesis Test on a Population Proportion - HL
State the Hypothesis Analyse sample data Interpret the results Step 2 – Analyse the sample data using a z-value We can standardise our p0 value using: This formula is not in Formulae and Tables. It is derived from an understanding of the standardising formula (p.34) and the standard error of the proportion (p.34). Step 3 - Interpret the results If |z|>1.96 it would indicate that p ≠ p0 at a 5% level of significance so we reject H0. If |z|<1.96 we fail to reject H0. Clearly state your conclusion. 1
108
Hypothesis Test on a Population Proportion - HL
State the Hypothesis Analyse sample data Interpret the results Step 2 – Analyse the sample data using a p-value Samples are normally distributed around p so we can standardise p0 using: Find P(Z ≤ |zp|) (p.36-37) Our p-value = 2(1 - P(Z ≤ |zp|) This formula is not in Formulae and Tables. It is derived from an understanding of the standardising formula (p.34) and the standard error of the proportion (p.34). Step 3 - Interpret the results If p-value < 0.05 it would indicate that p ≠ p0 at a 5% level of significance so we reject H0. If p-value > 0.05 we fail to reject H0. Clearly state your conclusion 4
109
95% Confidence Interval for a Population Mean - HL
Population mean Sample mean n Sample size σ Standard deviation If σ is unknown use s This formula is not given in Formulae and Tables is the z-value relating to a 95% level of confidence (p.37). The margin of error is the product of the z-value multiplier and the standard error of the mean (p.34): 2
110
95% Confidence Interval for a Sample Mean - HL
Population mean Sample mean n Sample size σ Standard deviation If σ is unknown use s This formula is not given in Formulae and Tables is the z-value relating to a 95% level of confidence (p.37). The margin of error is the product of the z-value multiplier and the standard error of the mean (p.34): 2
111
Hypothesis Test for a Sample Mean - HL
State the Hypothesis Analyse sample data Interpret the results Step 1 – State the Hypotheses State the null hypothesis (H0) and the alternative hypothesis (H1). H0:µ = µ0 H1: µ ≠ µ0 Population mean µ0 Hypothesised value of the population mean H0 is a statement of no change. We express it as a statement of equality. Note: Stating the alternative hypothesis as “not being equal” means that it could be either “less than” or “greater than” a value. This results in a two-tailed hypothesis test. 1
112
Hypothesis Test for a Mean - HL
State the Hypothesis Analyse sample data Interpret the results Step 2 Analyse the sample data using either a: Z-value P-value
113
Hypothesis Test for a Mean HL
State the Hypothesis Analyse sample data Interpret the results Step 2 – Analyse the sample data using a z-value Use the one-sample z-test (p.35): If σ is unknown use s Step 3 - Interpret the results If |z|>1.96 it would indicate that µ ≠ µ0 at a 5% level of significance so we reject H0. If |z|<1.96 we fail to reject H0. Clearly state your conclusion. 1
114
Hypothesis Test for a Mean - HL
State the Hypothesis Analyse sample data Interpret the results Step 2 – Analyse the sample data using a p-value Apply the one-sample z-test (p.35) : If σ is unknown use s Find P(Z ≤ |z|) (p.36-37) Our p-value = 2(1 - P(Z ≤ |z|) Step 3 - Interpret the results If p-value < 0.05 it would indicate that p ≠ p0 at a 5% level of significance so we reject H0. If p-value > 0.05 we fail to reject H0. Clearly state your conclusion. 2
115
Financial Maths Compound Interest Depreciation
Sum of Present Values (t1 = 0) Sum of Present Values (t1 ≠ 0) Sum of Future Values Amortisation
116
Financial Maths: Compound Interest
F = final value, P = principal Present value P = present value, F = final value p.30 p.30 Present Future 1
117
Financial Maths: Depreciation
- Reducing balance method F = later value, P = initial value p.30 Present Future 1
118
Series of equal withdrawals from fixed amount (Sum of Present Values)
where: a is the first term r is the common ratio Present value P = present value, F = final value p.30 p.22 Immediate first withdrawal Present Future 4
119
Series of equal withdrawals from fixed amount (Sum of Present Values)
P = present value, F = final value where: a is the first term r is the common ratio p.30 p.22 Delayed first withdrawal Present Future 4
120
Series of equal installments (Sum of Future Values)
where: a is the first term r is the common ratio Compound interest F = final value, P = principal p.30 p.22 Present Future 4
121
Financial Maths: Amortisation
Amortisation – mortgages and loans (equal repayments at equal intervals) A = annual repayment amount P = principal p.31
122
Functions Calculus Mapping Functions Table and Mapping
Table (and Graph) Mapping Diagrams Graph given Table Comparing Functions Composite Functions Types of Functions Calculus Differentiation Integration
123
Function Machine with Mapping Diagram
1
124
Function Machine with Table and Mapping Diagram
1
125
Functions: Table and Graph
Function: Domain: Table Function machine 4
126
Mapping Diagrams 3
127
Investigating Functions with a Mapping Diagram and Graph
Function: Domain: 4
128
Graphing a Function from a Table
Function: Domain: 4
129
Comparing Functions - Simultaneous Functions
Domain: 4
130
Composite Functions Function: Function: Function machines
Mapping Diagram Table 2
131
Differential Calculus
p.25
132
Integral Calculus p.26
133
Fraction Wall – Comparing Fractions
5
134
Length, Area and Volume Parallelogram Trapezium Circle/Disc Arc/Sector
Triangle Cylinder Cone Sphere Frustum of Cone Prism Pyramid Trapezoidal Rule
135
Length & Area: Parallelogram
136
Length and Area of a Trapezium
137
Length of a Circle and Area of a Disc
p.8
138
Length of an Arc and Area of a Sector
p.9
139
Length and Area of a Triangle
p.9
140
Surface Area and Volume of a Cylinder
p.10
141
Surface Area and Volume of a Cone
p.11
142
Surface Area and Volume of a Sphere
143
Surface Area and Volume of a Frustum of Cone
p.12
144
Surface Area and Volume of a Prism
145
Surface Area and Volume of a Pyramid
146
Area Approximations: Trapezoidal Rule
147
Trigonometry Pythagoras Trig Ratios Sine Rule Cosine Rule
Area of a Triangle Identities… Unit Circle Angle Ratios Compound Angle Double Angle Product & Sums Trig. Functions
148
Pythagoras’ Theorem p.16
149
Trigonometric Ratios p.16
150
The Sine Rule p.16 sine rule
151
The Cosine Rule p.16 cosine rule
152
Area of a Triangle p.16 area
153
Compound Angle Formulae
154
Double Angle Formulae p.14
155
Trigonometric Products and Sums/Differences
156
Trigonometry: Identities & Definitions
p.13 sec2 A = 1 + tan2 A
157
Trigonometry: The Unit Circle
p.13
158
Trigonometric Ratios of certain angles
p.13
159
Geometry Synthetic Geometry Co-ord. Geometry
160
Synthetic Geometry Theorems Constructions Enlargements Axial Symmetry
Central Symmetry Rotations
161
Geometry Theorems Theorem ____: 1. Diagram: 4. To Prove: 5. Proof: 2. Given: 3. Construction:
162
Geometry Construction
163
Construct: The perpendicular bisector of [AB]
Geometry Construction Construct: The perpendicular bisector of [AB] A B
164
Geometry: Enlargements
Centre of Enlargement Centre of Enlargement 3
165
Geometry Transformations: Axial Symmetry
Axis of symmetry Axis of symmetry Axis of symmetry 3
166
Geometry Transformations: Central Symmetry
Centre of Symmetry Point of Reflection 1
167
Geometry Transformations: Rotations
Point of Rotation 3
168
Co-ordinate Geometry of the Line
Line Formulae Area of Triangle Distance to line, Angle & Division Co-ordinate Geometry of the Circle Centre (h, k) Centre (-g, -f)
169
Co-ordinate Geometry of the Line
p.18 1
170
Co-ordinate Geometry: Area of a Triangle
p.18 1
171
Co-ordinate Geometry of the Line (LCHL)
p.19 1
172
Co-ordinate Geometry: Circle
p.19 1
173
Co-ordinate Geometry: Circle
p.19 1
174
Number Systems Venn Diagram
p.23 C R Q Z N Z\N Q\Z R\Q C\R 3
175
Indices p.21
176
Logarithms p.21
177
Sequences and Series Arithmetic Geometric
178
Arithmetic Sequence and Series
p.22 In the following Tn is the nth term, and Sn is the sum of the first n terms where a is the first term and d is the common difference.
179
Geometric Sequence and Series
p.22 In the following Tn is the nth term, and Sn is the sum of the first n terms where a is the first term and r is the common ratio.
180
Homework Assignment and Notes
Date: Notes: Maths Homework: Due:
Similar presentations
© 2025 SlidePlayer.com. Inc.
All rights reserved.