The concept of **Bell** comes from late Latin *Bell*, in turn linked to the Italian region of **Campania** . There were used for the first time **bells** , which are metal instruments with an inverted cup shape that are beaten so that they emit a sound. Objects with **similar form** to these **instruments** They also receive the name bell.

**Gauss** , meanwhile, is the last name of a physicist and mathematician (**Carl Friedrich Gauss** ) That was born in **1777** in **Brunswick** and he died in **1855** in **Göttingen** . His scientific contributions have marked the development of **mathematics** .

The notion of **gauss bell** refers to the **graphic representation** of a statistical distribution linked to a **variable** . This representation has the shape of a bell.

The **gauss bell** graph one **gaussian function** , which is a kind of mathematical function. This bell shows how the **probability** of a continuous variable.

The concept of **mathematical function** It can be defined as the relationship between two quantities or quantities such that one depends on the value of the other. Each of them must belong to a **set** different: one is known by the name of *domain*, and the other one is called *codomain*; each element of the first corresponds only to each other.

We can understand the mathematical functions with a simple example: the duration of a trip between two geographical points depends on the speed at which the body moves, which should be included in a **equation** along with the distance. In this particular case, speed and duration vary inversely proportionally: the larger one is, the lower the other.

Another of the concepts that appears in the context of the Gaussian bell is the **Continuous variable** . To explain it is necessary to start by defining **discrete variable** , which is the one that does not accept a **value** "intermediate" between those exposed in a given set, but only those observed in it; for example, if we want to count the number of people in a room, the result will always be whole (such as, *3* or *4*, but never *3.2*).

The notion of **Continuous variable** On the other hand, it does accept these values, and that is why its application is very different. For example, measuring the height of a human being yields such a variable, and the accuracy of the result always depends on the instrument used, which is why we must contemplate a certain margin of error.

In the **gauss bell** a medium zone (concave and with the average value of the **function** in its center) and two extremes (convex and with a tendency to approach the **X axis** ). This distribution shows how the values of variables behave whose changes are due to random phenomena. The most common values appear in the center of the bell and the least frequent, at the ends.

With the **gauss bell** for example, the average income of the economically active population of a region can be analyzed **X** . While there are **people** that in that territory they win **$ 10 per month** and others that receive more than **1 000 000** , most individuals get between **5 000** and **$ 10,000** . Those values will focus on the center of the **gauss bell** .

Another name by which Gauss's bell is known is **normal distribution** . One of the reasons for its importance is that it relates to a very significant estimation method called *Least Squares*, used for a long time to optimize a series of ordered pairs to find a continuous function that is closest to them; In simpler terms, given a set of data, this technique seeks to "adjust" them to a "clean" line, accepting a certain margin of error.