The mean as measure of location takes the form z=∑ where o i and zi refer to the relatively frequency and the midpoint of interval i The mode as a measure of location refers to the value of income that occurs most frequently in the data set. Another measure of location is the median referring to the value of income in the middle when income are arranged in an ascending order according to the size of income. The best way to calculate the median is to plot the cumulative frequency grap Another important feature of the histogram is the dispersion of the relative frequency around a measure of central tendency. The most frequently used mea- sured of dispersion is the variance defined by ∑(a1-2) which is a measure of dispersion around the mean; v is known as the standard deviation We can extend the concept of the variance to i=1 defining what are known as higher central moments. These higher moments can be used to get a better idea of the shape of the histogram. For example, the standardized form of the third and fourth moments defined by known as the skewness and kurtosis coef ficients, measure the asymmetry and the peakedness of the histogram, respectively. In the case of a symmetric his- togram, SK=0 and the less d the histogram the 1.2 Looking Ahead The most important drawback of descriptive statistics is that the study of the observed data enables us to draw certain conclusions which relate only to theThe mean as measure of location takes the form z¯ = Xn i=1 φizi , where φi and zi refer to the relatively frequency and the midpoint of interval i. The mode as a measure of location refers to the value of income that occurs most frequently in the data set. Another measure of location is the median referring to the value of income in the middle when income are arranged in an ascending order according to the size of income. The best way to calculate the median is to plot the cumulative frequency graph. Another important feature of the histogram is the dispersion of the relative frequency around a measure of central tendency. The most frequently used mea￾sured of dispersion is the variance defined by v 2 = Xn i=1 (zi − z¯) 2φi , which is a measure of dispersion around the mean; v is known as the standard deviation. We can extend the concept of the variance to mk = Xn i=1 (zi − z¯) kφi , k = 3, 4, ... defining what are known as higher central moments. These higher moments can be used to get a better idea of the shape of the histogram. For example, the standardized form of the third and fourth moments defined by SK = m3 v 3 and K = m4 v 4 , known as the skewness and kurtosis coefficients, measure the asymmetry and the peakedness of the histogram, respectively. In the case of a symmetric his￾togram, SK = 0 and the less peaked the histogram the greater value of K. 1.2 Looking Ahead The most important drawback of descriptive statistics is that the study of the observed data enables us to draw certain conclusions which relate only to the 2