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Biostatistics for Animal Science

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8 <strong>Biostatistics</strong> <strong>for</strong> <strong>Animal</strong> <strong>Science</strong><br />

The Median of a sample of n observations y1,y2,...,yn is the value of the observation that is in<br />

the middle when observations are sorted from smallest to the largest. It is the value of the<br />

observation located such that one half of the area of a histogram is on the left and the other<br />

half is on the right. If n is an odd number the median is the value of the (n+1) /2-th<br />

observation. If n is an even number the median is the average of (n) /2-th and (n+2) /2-th<br />

observations.<br />

The Mode of a sample of n observations y1,y2,...,yn is the value among the observations that<br />

has the highest frequency.<br />

Figure 1.4 presents frequency distributions illustrating the mean, median and mode.<br />

Although the mean is the measure that is most common, when distributions are asymmetric,<br />

the median and mode can give better in<strong>for</strong>mation about the set of data. Unusually extreme<br />

values in a sample will affect the arithmetic mean more than the median. In that case the<br />

median is a more representative measure of central tendency than the arithmetic mean. For<br />

extremely asymmetric distributions the mode is the best measure.<br />

frequency<br />

mean<br />

(balance point)<br />

frequency<br />

50% 50% frequency<br />

median<br />

Figure 1.4 Interpretation of mean, median and mode<br />

1.4.3 Measures of Variability<br />

mode<br />

maximum<br />

Commonly used measures of variability are the range, variance, standard deviation and<br />

coefficient of variation.<br />

Range is defined as the difference between the maximum and minimum values in a set of<br />

observations.<br />

Sample variance (s 2 ) of n observations (measurements) y1, y2,...,yn is:<br />

2<br />

( − )<br />

2<br />

=<br />

− 1<br />

∑ y y<br />

i i<br />

s<br />

n<br />

This <strong>for</strong>mula is valid if y is calculated from the same sample, i.e., the mean of a population<br />

is not known. If the mean of a population (µ) is known then the variance is:<br />

∑ y<br />

i i<br />

s<br />

n<br />

−<br />

2<br />

( µ<br />

)<br />

2<br />

=

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