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Logbook activity - discrete and continuous data

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By: Anjni Varsani - M00073861 Quanitive Methods and applications for business management - STX1115 Bill Francis Logbook Activity 1 There are two types of data variables which are: discrete and continuous data. A variable is something which can change in value and it is usually numeric, but not always. Discrete data is where there are individual values; the values are unique and distinct from the other. It can measure something precisely for example shoe size or the number of siblings someone may have. A continuous variable can be any value for example height or the time in seconds it took for an athlete to run a 100metre race. It can vary from a small number to a large number. Sometimes the distinction between a discrete and a continuous variable is unclear. For example a person's age is a continuous variable as someone can be 21.34342 years old. This is measuring age accurately. However we don't actually say our age in decimal points, we would say in this case that someone is 21 instead of 21.34342 years old. ...read more.


Essentially a histogram is similar to a bar chart but histograms have all the bars joined up as it is showing continuous data and represent frequency distributions. Also in a bar chart there all the widths are the same. However in a histogram they don't necessarily have to be because it is the area of bars that are focused on a histogram. One main advantage that a histogram has is that is shows the shape of the distribution for a large set of data so it is visually strong and easily understandable (as it is continuous); this is the reason why I chose to create a histogram graph of the data given to me. But the biggest disadvantage is that data can be lost because it is grouped. Another disadvantage is that it can be very difficult to compare two data sets. This graph shows that most peoples heights are grouped around the 170 - 180 mark. There are very few people who are 200cm and also very few that are 130-140cm. the table is generally going up and then back down in a pyramid shape. ...read more.


many things to compare. There is also limited space for labelling on vertical graphs. 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. Range = 10 13-3 = 10 Mode = 5 Median = 7 Mean average = 7.09314 rounded down to 7. ...read more.

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