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Analysing data

Analysing data

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Data can be made easier to interpret be calculating different averages, which are called measures of central tendency. The three main measures of central tendency are the mean, the mode and the median. The mean can be found by calculating the sum of the values of the data and dividing by how many values there are. The median can be by taking the middle value when all the values are put into order from smallest to largest. When there are an even number of values in the set of data, there will be two middle values, and thus the median can be found by calculating the average of those two values. The mode of a set of values is the value that appears most often. If the values are separated into classes, the modal class is the most common one.

Central tendency

The range of a set of values is used to describe the spread of the data. The range can be calculated by subtracting the smallest value in the set from the largest value. The range is affected by outliers in the data, which are values which do not follow the pattern of the rest of the data. A more accurate value of the range can be found if it is calculated by removing outliers.

Spread of data

Quartiles are another measure of spread. The lower quartile is the median of the lower half of the data and it is found by taking the (n+1)/4 value, where n is the number of values in the data. The upper quartile is the median of the upper half of the data and it is found by taking the 3(n+1)/4 value. If there are an even number of values, the quartile is found by taking the average of the two middle values.

Quartiles

The interquartile range (IQR) is the difference between the lower and upper quartile. The IQR is a measure of spread which is not affected by outliers, unlike the range of the set of values.

Inter-quartile range

Standard deviation is a measure of spread which gives a quantitative measure of how much the values of a set differ from their mean value. The difference between each value and the mean is found and is squared. These squared differences are then added together and divided by the number of values in the set. Taking the square root of this gives the standard deviation.

Standard deviation

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