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**Concept of descriptive statistic:**

The concept of descriptive statistic has distinguished from inferential statistics. The descriptive statistic is the way of summarizing the quantitative data or information. It has not developed from probability theory.

Some commonly used measures to describe the set of data are the measure of central tendency and measure of variability or dispersion. The measure of central tendency includes mean, medium and mode. The measure of dispersion includes the standard deviation or variance, minimum and maximum of variables, kurtosis and skewness.

**Mean:**Mean or arithmetic mean are derived by obtaining the sum of all measurements by dividing the number of observations in the data set.**Median:**Median is derived by taking the middle value that separates the higher half value from the lower half of the data set.**Mode:**It is derived by taking highest frequency of the value out from the data set.

**Sub division of mean:** Again mean is subdivided into simple arithmetic mean, harmonic mean and geometric mean.

**Simple arithmetic mean:**

Simple arithmetic mean is derived by dividing the sum of all measurement by the number of observation. It can be illustrated in the following way:

Marks (x) |

50 |

60 |

50 |

This sum can be solved easily by using the formula: sum of x/ number of observation, so it will be 50+60+50= 160, divide it by 3 which is the number of observation, the result will be 53.3.

**Harmonic mean:**

This measure is valid only for the data that are measured absolutely on a strictly real scale.

**Geometric mean:**

This measure too is valid only for the data that are measured absolutely on a strictly real scale. It is classified in simple geometric mean and weighted geometric mean.

Among all the measures, central tendency covers a wide range of topic. All these sums are based on formula and concept. Without learning the formula, you cannot proceed for the sum.

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