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In Statistics , the term ''central tendency'' is used in some fields of Empirical Research to refer to what statisticians sometimes call "location". A "measure of central tendency" is either a Location Parameter or a Statistic used to estimate a location parameter.


MEASURES OF CENTRAL TENDENCY

There are several different kinds of calculations for central tendency, the kind of calculation that should be used depends on the type of data ( Level Of Measurement ) and purpose for which the central tendency is being calculated:
  "http://wwwinformationdelightinfo/information/entry/Quadratic_mean" class="copylinks">Quadratic Mean <br>(or RMS) <math>\sqrt{ rac{1}{n} \sum_{i=1}^{n} x_i^2} =



  "http://wwwinformationdelightinfo/information/entry/Generalized_mean" class="copylinks">Generalized Mean <math>\sqrt {Link without Title} { rac{1}{n} \cdot \sum_{i=1}^n x_{i}^p}</math>
  "http://wwwinformationdelightinfo/information/entry/Heronian_mean" class="copylinks">Heronian Mean <math> rac{2}{n(n+1)} \cdot \sum_{i=1}^n \sum_{j=1}^n \sqrt{x_i x_j}</math>
  "http://wwwinformationdelightinfo/information/entry/Weighted_mean" class="copylinks">Weighted Mean <math> rac{ \sum_{i=1}^n w_i x_i}{\sum_{i=1}^n w_i} = rac{w_1 x_1 + w_2 x_2 + \cdots + w_n x_n}{w_1 + w_2 + \cdots + w_n}</math>
  "http://wwwinformationdelightinfo/information/entry/Truncated_mean" class="copylinks">Truncated Mean The arithmetic mean of data values after a certain number or proportion of the highest and lowest data values have been discarded
  "http://wwwinformationdelightinfo/information/entry/Interquartile_mean" class="copylinks">Interquartile Mean A special case of the truncated mean, using the Interquartile Range
  "http://wwwinformationdelightinfo/information/entry/Midrange" class="copylinks">Midrange <math> rac{\max x + \min x}{2}</math>
  "http://wwwinformationdelightinfo/information/entry/Winsorized_mean" class="copylinks">Winsorized Mean Similar to the truncated mean, but, rather than deleting the extreme values, they are set equal to the largest and smallest values that remain