The outer fence (usually not marked) is at a distance of three times the IQR on either side of the box. If the data are sparse on one side, the corresponding side whisker will be short. If the distribution is symmetrical, then the whiskers are of equal length. The end of whiskers is called the inner fence and any value outside it is an outlier. These whiskers are 1.5 times the length of the box, i.e., the interquartile range (IQR). The lines outside the box on either side are known as whiskers. If the median is closer to the upper quartile, then they are negatively skewed and if it is near the lower quartile, then positively skewed. The position of the median indicates whether the data are skewed or not.
The line inside the box denotes the median (sometimes marked as a plus sign). The length of the box indicates the variability of the data. Hence the middle 50% of observations are represented by the box. There is a vertical or horizontal rectangle (box), the ends of which correspond to the upper and lower quartiles (75 th and 25 th percentile, respectively). This graph, first described by Tukey in 1977, can also be used to illustrate the distribution of data. It also gives the cumulative and relative frequency that helps to interpret the data more easily. The frequency distribution table of the resting pulse rate in healthy individuals is given in Open-ended classes at the lower and upper side (e.g., 100) should be avoided. The class intervals should be mutually exclusive and nonoverlapping. Unequal class widths should be used only when large gaps exist in data. It is advisable to have equal class widths. The following are some guidelines regarding class widths: The width of the class can be determined by dividing the range of observations by the number of classes. On the other hand, if they are very few, then the shape of the distribution itself cannot be determined. The range is divided into arbitrary intervals called “class interval.” If the class intervals are too many, then there will be no reduction in the bulkiness of data and minor deviations also become noticeable. Before constructing a frequency table, one should have an idea about the range (minimum and maximum values). A frequency (distribution) table shows the different measurement categories and the number of observations in each category.
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