Describing Distributions of Data

An analyst has been asked to determine the cholesterol concentration in a particular tub of low-fat spread. The analyst takes ten samples from the tub and determines the cholesterol concentration in each sample. The results are shown in Table 6.1. 

The normal distribution describes the way measurement results are commonly distributed. This type of distribution of data is also known as a Gaussian distribution. Most measurement results, when repeated a number of times, will follow a normal distribution. In a normal distribution, most of the results are clustered around a central value with fewer results at a greater distance from the centre. The distribution has an infinite range, so values may turn up at great distances from the centre of the distribution although the probability of this occurring is very small. 

A normally distributed population of data can be characterized by two parameters. The centre, or location, of the population is described by the parameter i 

In a normal distribution of data, 68.3% of the values lie within 1 standard deviation of the mean value while 95.4% of the values lie within 2 standard 

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