Curriculum
- 4 Sections
- 132 Lessons
- 365 Days
- 1. Numbers32
- 1.11.1.1 Types of numbers
- 1.21.1.3 Mathematical Operations
- 1.31.1.4 Number Operations
- 1.41.1.5 Prime Factor Decomposition
- 1.51.2.1 Set Notation
- 1.61.2.2 Venn Diagrams
- 1.71.3.1 Powers/Indices and roots
- 1.81.3.2 Standard Form
- 1.91.3.3 Working with standard form
- 1.101.4.1 Fractions
- 1.111.4.2 Working with Fractions
- 1.121.4.3 Decimals
- 1.131.5.1 Percentage
- 1.141.5.2 Working with Percentage
- 1.151.6.1 Conversions
- 1.161.6.2 Ordering
- 1.171.7.1 Ratios
- 1.181.7.2 Working with Ratios
- 1.191.8.1 Proportion
- 1.201.9.1 Rounding
- 1.211.9.2 Estimation
- 1.221.9.3 Bounds
- 1.231.10.1 Using a Calculator
- 1.241.11.1 Time
- 1.251.11.2 Currency
- 1.261.11.3 Currency Conversion
- 1.271.12.1 Simple Interest
- 1.281.12.2 Compound interest
- 1.291.12.3 Depreciation
- 1.301.13.1 Exponential growth
- 1.311.13.2 Exponential decay
- 1.321.14.1 Compound measures
- 2. Algebra and Graphs39
- 2.12.1.1 Algebra Notation
- 2.22.1.2. Algebra Vocabulary
- 2.32.1.3. Algebra Basic
- 2.42.2.1 Algebraic roots & Indices
- 2.52.3.1 Expanding brackets
- 2.62.3.2 Factorisation
- 2.72.3.3 Quadratic expressions
- 2.82.3.4 Difference of two squares
- 2.92.4.1 Linear Equations
- 2.102.4.2 Linear Inequalities
- 2.112.5.1 Quadratic Equations
- 2.122.6.1 Rearranging formula
- 2.132.7.1 System of Linear Simultaneous Equations
- 2.142.7.2 System of quadratic simultaneous equations
- 2.152.8.1 Algebraic fractions
- 2.162.8.2 Working with algebraic fractions
- 2.172.8.3 Solving algebraic fractions
- 2.182.9.1 Forming equations
- 2.192.9.2 Equations & Problem solving
- 2.202.10.1 Introduction to functions
- 2.212.10.2 Composite & Inverse functions
- 2.222.11.1 Sequences
- 2.232.11.2 nth term
- 2.242.12.1 Midpoint of a line
- 2.252.12.2 Gradient of a line
- 2.262.12.3 Length of a line
- 2.272.13.1 Linear Graph
- 2.282.13.2 Quadratic Graphs
- 2.292.14.1 Types of Graphs
- 2.302.14.2 Drawing a graph without using a calculator
- 2.312.14.3 Drawing a graph with a calculator
- 2.322.14.4 Using a graph
- 2.332.14.5 Tangents
- 2.352.15.1 Drawing a Graph
- 2.362.15.2 Interpreting graphical inequalities
- 2.372.16.1 Distance-Time Graph
- 2.382.16.2 Speed-Time Graph
- 2.392.17.1 Differentiation
- 2.402.17.2 Applications
- 3. Geometry36
- 3.03.1.1 Symmetry
- 3.13.1.2 2D Shapes
- 3.23.1.3 3D shapes
- 3.33.1.4 Unit conversions
- 3.43.2.1 Basic angle Properties
- 3.53.2.2 Angle properties with triangle
- 3.63.2.3 Angle properties with quadrilateral
- 3.73.2.4 Angles in polygon
- 3.83.3.1 Bearings
- 3.93.3.2 Scale
- 3.103.3.3 Constructing SSS triangle
- 3.113.4.1 Angles at center & Semicircles
- 3.123.5.1 Perimeter
- 3.133.5.2 Area
- 3.143.5.3 Problems Solving with Areas
- 3.153.6.1 Arc
- 3.163.6.2 Sector
- 3.173.7.1 Volume
- 3.183.7.2 Surface area
- 3.193.8.1 Congruence
- 3.203.8.2 Similarity
- 3.213.9.1 Pythagoras Theorem
- 3.223.9.2 Right-angled Trigonometry
- 3.233.10.1 Sine Rule
- 3.243.10.2 Cosine Rule
- 3.253.10.3 Area of Triangle
- 3.263.10.4 Applications of Trigonometry
- 3.273.11.1 Pythagoras in 3D
- 3.283.12.1 Drawing trigonometric graph
- 3.293.12.2 Solving trigonometric equations
- 3.303.13.1 Basic Vectors
- 3.313.13.2 Vector problem solving
- 3.323.14.1 Translation
- 3.333.14.2 Rotation
- 3.343.14.3 Reflection
- 3.353.14.4 Scaling
- 4. Probability and Statistics25
- 4.04.1.1 Basic probability
- 4.14.1.2 Relative Frequency
- 4.24.1.3 Expected Frequency
- 4.34.2.1 Two way Tables
- 4.44.2.2 Probability & Venn Diagram
- 4.54.2.3 Tree Diagram
- 4.64.3.1 Conditional probability
- 4.74.3.2 Combined conditional probabilities
- 4.84.4.1 Mean, median & mode
- 4.94.4.2 Averages from Tables and Charts
- 4.104.4.3 Averages from Grouped Data
- 4.114.4.4 Comparing Distributions
- 4.124.5.1 Stem & Leaf diagrams
- 4.134.5.2 Bar chart
- 4.144.5.3 Pictogram
- 4.154.5.4 Pie chart
- 4.164.5.5 Frequency polygon
- 4.174.5.6 Working with Statistical Diagram
- 4.184.6.1 Frequency Density
- 4.194.6.2 Histograms
- 4.204.7.1 Cumulative frequency
- 4.214.7.2 Box-and-whisker Plots
- 4.224.8.1 Correlation
- 4.234.8.2 Scatter Graph
- 4.244.8.3 Line of best Fit
4.5.5 Frequency polygon
A frequency polygon is a type of graph used to represent a frequency distribution of a set of continuous data.
It is constructed by joining the midpoints of the top of each rectangle in a histogram with straight lines.
The x-axis represents the range of the data, which is divided into equal intervals or bins, while the y-axis represents the frequency or the number of data points that fall into each bin.
The frequency polygon can help to visualize the shape of the distribution and identify any patterns or trends in the data.
In summary, a frequency polygon is a graphical representation of a frequency distribution that shows the frequencies of values in a dataset with connected line segments.
Some key features of a frequency polygon are
X-axis : The horizontal axis represents the range of values in the dataset.
Y-axis : The vertical axis represents the frequency or the number of occurrences of values in the dataset.
Points : The frequency polygon is constructed by connecting points on the graph. The points are located at the midpoint of the interval on the \( x \)-axis and at the height of the corresponding frequency on the \( y \)-axis.
Line : The line connecting the points creates a polygon-like shape.
Shape : The shape of the frequency polygon can provide information about the distribution of the dataset. For example, a bell-shaped curve would indicate a normal distribution.
Area : The area under the curve of the frequency polygon represents the total number of observations in the dataset.
Axis labels : The \( x \) and \( y \)-axes are labeled to indicate the units of measurement and the range of values represented on the graph.
Overall, a frequency polygon is a useful tool for visualizing the distribution of a dataset and identifying patterns in the data.
Worked example:
Let’s say we have a dataset of exam scores for a class of \( 30 \) students.
The scores range from \( 60 \) to \( 100 \) and are given in \( 5 \) point intervals.
Find the midpoint of each interval
Plot the midpoint of each interval on the \( x \)-axis and the frequency on the y-axis.
The resulting graph looks like this:
In this example, the \( x \)-axis represents the score ranges, and the \( y \)-axis represents the frequency of each score range.
The points are connected by a line to form the frequency polygon.
We can see that the highest frequency occurs in the \( 80 \)-\( 84 \) score range, and the distribution of scores is somewhat skewed to the right.
The area under the curve of the frequency polygon represents the total number of exam scores in the dataset, which is \( 30 \) in this example.