Practise drawing and reading information from histograms displaying grouped data
This is level 1: show the height of one bar in an almost-complete histogram with fixed class intervals. You can earn a trophy if you get at least 4 questions correct and you do this activity online.
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Reading Graphs and Charts - Answer real-life problems from different types of graphs and charts including piece-wise linear graphs.
Level 1 - Show the height of one bar in an almost-complete histogram with fixed class intervals
Level 2 - Read information from histograms with fixed class intervals
Level 3 - Complete a frequency table with information from a histogram with unequal class intervals
Level 4 - Complete a frequency table with information from a histogram showing frequency density
Level 5 - General questions about histograms with varying class widths
Exam Style Questions - A collection of problems in the style of GCSE or IB/A-level exam paper questions (worked solutions are available for Transum subscribers).
More on this topic including lesson Starters, visual aids, investigations and self-marking exercises.
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Histograms are similar to bar charts but there is one important difference. It is the area of the bars in a histogram that is proportional to the frequency rather than the height.
The first couple of levels of this exercise features histograms with equal class widths which means the heights of the bars can be conveniently used to find the frequency.
Levels 3 onwards contain histograms with unequal class widths so the vertical axis can be thought of as the frequency density.
Frequency = Frequency density × Class Width
Histograms can be used to represent both discrete and continuous data but they are typically used for displaying continuous data.
To draw a histogram, the data first needs to be assigned to a number of different groups (classes or bins). There are various theories concerning how many of these groups there should be but the normal is between five and twenty depending on the amount of data. A number of consecutive groups containing very little data may be merged into a single group.
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