Measures of Central Tendency:
Most frequency distributions exhibit a Central tendency means a shape such that the bulk of the observations pile up in the area between the two extremes. The measure of this central tendency is one of the two most fundamental measures in all statistical analysis. There are three principal measures of central tendency.
Mean (X̅):
The mean is calculated by adding the observations and dividing by the number of observations. Arithmetic mean is used for symmetrical or near symmetrical distributions or for distributions which lack a clear dominant single peak. The arithmetic mean, X, is the most generally used measure in quality work.
Median:
It is the middle-most or most central value when the figures (data) are arranged according to size. Half of the items lie above this point and half lie below it. It is used for reducing the effects of extreme values, or for data which can be ranked but are not economically measurable or for special testing situations. To find the median of a data set, just array the data in ascending or descending order. If the data set contains an odd number of items, the middle item of the array is the median. If there is an even number of items, the median is the average of the two middle items. In formal language, the
Mode:
It is the value which occurs most often in data set. It is used for severely skewed distributions, describing irregular situations where two peaks are found, or for eliminating the effects of extreme values.
Estimation:
Statistical quality control tells what should be the sample size and how much reliable will be that sample. (A criteria can be decided on the basis of which a lot will be accepted or rejected).
A common thing in statistics is the Estimation of parameters on the basis of a sample. A sample mean is generally not enough as its value may not be same as the mean size of the total lot, out of which the sample is drawn. Thus, it is better to indicate the reliability of the estimates and provide limits which may be expected to contain the true value.
