ORGANISING, REPRESENTING AND INTERPRETING DATA
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Subject: Additional Mathematics
Class: SHS 1
Term: 2nd Term
Week: 15
Grade code: 1.4.1.LI.5
Strand code: 4
Sub-strand code: 1
Content standard code: 1.4.1.CS.1
Indicator code: 1.4.1.LI.5
Theme: HANDLING DATA
Subtheme: ORGANISING, REPRESENTING AND INTERPRETING DATA
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In our daily lives in Ghana, we are surrounded by data. The Ghana Statistical Service collects data on population, the Ministry of Food and Agriculture collects data on crop yields, and even in our schools, we collect data on student performance. To make sense of all this information, we need powerful tools to organise and visualise it. This lesson focuses on two key graphical tools for grouped data: the Histogram (especially for data with unequal class widths) and the Cumulative Frequency Curve (Ogive). Mastering these skills will allow you to tell a clear story from a set of numbers and make informed decisions.
Part 1: The Histogram - A Quick Recap and A New Challenge
A Histogram is a graphical representation of the distribution of numerical data. It looks like a bar chart, but there are important differences: It is used for continuous data (data that can take any value within a range, like height, weight, or time). The bars are joined together to show that the data is continuous. The horizontal axis (x-axis) represents the continuous variable, while the vertical axis (y-axis) represents the frequency. The area of each bar is proportional to the frequency of that class.
Case 1: Histograms with Equal Class Intervals (Recap) When the class intervals (or class widths) are all the same, the height of each bar is directly proportional to the frequency. We simply plot frequency on the y-axis.
*Example:* The marks of 30 students in a quiz were recorded as follows. | Marks | 0-10 | 10-20 | 20-30 | 30-40 | 40-50 | |---|---|---|---|---|---| | Frequency | 4 | 7 | 10 | 6 | 3 |