PDF | On Jul 1, , S Manikandan and others published Measures of central tendency: Median and mode. Apart from the mean, median and mode are the two commonly Advantages. 1. It is easy to Disadvantages. 1. Merits or Uses of Median: 1. Median is rigidly defined as in the case of Mean. 2. Even if the value of extreme item is much different from other values, it is not. Merits or Uses of Mode: 1. Mode is the term that occur most in the series hence it is not an isolated value like Median nor it is value like mean that not be.
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The Educational Advantage Explain how mean, median, and mode can be affected by extreme data values. . A disadvantage of the mean, however, is. Measures of central tendency: Median and mode Apart from the mean, median and mode are the two commonly used measures of central Disadvantages. The mean, median and mode are the three commonly used measures of central tendency. The important disadvantage of mean is that it is sensitive to extreme .
Median is rigidly defined as in the case of Mean.
Even if the value of extreme item is much different from other values, it is not much affected by these values e. Median in case of 4, 7, 12, 18, 19 is 12 and if we add two values equal to , new median is M; as is in case of intelligence etc. It is possible to arrange in any order and to locate the middle valve. For such cases it is the best measure.
It can be located graphically. For open end intervals, it is also suitable one. As taking any value of the intervals, value of Median remains the same.
It can be easily calculated and is also easy to understand 7.
Median is also used for other statistical devices such as Mean Deviation and skewness. There are different types of mean, viz.
If mentioned without an adjective as mean , it generally refers to the arithmetic mean. It is computed by adding all the values in the data set divided by the number of observations in it. The research articles published in journals do not provide raw data and, in such a situation, the readers can compute the mean by calculating it from the frequency distribution if provided.
Open in a separate window Where, f is the frequency and X is the midpoint of the class interval and n is the number of observations. Readers are cautioned that the mean calculated from the frequency distribution is not exactly the same as that calculated from the raw data.
It approaches the mean calculated from the raw data as the number of intervals increase. The irony in this is that most of the times this value never appears in the raw data.
Repeated samples drawn from the same population tend to have similar means. The mean is therefore the measure of central tendency that best resists the fluctuation between different samples.
Even though mean can be calculated for numerical ordinal data, many times it does not give a meaningful value, e. Weighted mean Weighted mean is calculated when certain values in a data set are more important than the others.
For example, When weighted mean is used to represent the average duration of stay by a patient in a hospital, the total number of cases presenting to each ward is taken as the weight.