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A discrete variable is where the data is countable and cannot usually be in more than one decimal point. Shoe size is a variable which can be a continuous variable as you can measure it to the exact centimetre. However you would not say that someone’s shoe size is size 8.1443; it would be 8. Therefore shoe size is a discrete variable. A bar chart is used to highlight separate data quantities and shows the differences.

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“It is a graph made of bars whose heights represent the frequencies of respective categories.” (Source: ‘introductory statistics’ by Prem S Mann, Fifth Edition) The main advantages of a bar chart are that it is visually strong and understandable and it is excellent for data comparison. Also data is not lost as it is on a histogram and bar graphs clearly show error values on the data. many things to compare. There is also limited space for labelling on vertical graphs.

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The disadvantages are it may sometimes become difficult to understand as it could be congested with too much information. There are two sets of data I found which were size 38 and there are two and 44. This may be people who responded to their shoe size by European size. So I simply converted this to U.K size.

This bar graph shows that the most common shoe size is 5 – where there are 41 people. There are very few half shoe sizes, this may be a results of the way the question was asked in the survey. Many people may have thought that they had to respond in a full size. The shoe size with the least value is size 3.5, 10 and 13. Overall data that is shown can be sometimes misleading. However if it is presented in the correct graph and it is showing what it is meant to show then graphs can be very useful. Mean average = 7.09314 rounded down to 7. Lower quartile range = rounded down to size Upper quartile range = rounded up to Interquartile range =

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