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Statistics |
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Descriptive Statistics is the branch of statistics that concerns collecting data, analysing it and presenting the results graphically or via the calculation of statistical parameters, numbers used to describe a set of data. However, it is often not possible to obtain the value of a variable for every member in of population. In such a case data is collected from a sample, or a portion of the population, and used to infer information about the characteristics of the population as a whole. This is the situation to which the procedures described in this chapter are best suited. On other occasions observations in Descriptive Statistics relate to the values observed when carrying out a random experiment. In such a case the objective of the sample results is to try to establish a theoretical model which governs the experiment. In Statistics, wiris always works with decimal numbers, unlike other areas of knowledge. This is done in order to follow the norms of practice in this area. Take a look at how a sample consisting of 3 zeros and 4 ones can be represented.
In the first case a List, which contains the elements of a sample, was considered, and in the second case, a Divisor was used to indicate how may times each value appears. Now let's look at some operations we can carry out with samples.
To finish the introduction, it should be noted that it is possible to group different samples of random variables using a Divisor. A detailed explanation of this functionality can be found in the Multisample description in the alphabetical index. Before proceeding let's look at some examples to clarify what we mean:
In this section we explain the functions that wiris can apply to a data set (observations from a statistical variable), x={x1,x2,...,xn}.
wiris has various functions that accept samples with bivariate data as the argument, i.e. a sample of the following form (x1,y1),(x2,y2),...,(xn,yn). Notice from the examples below that, although data entry can be carried out independently for the first and second variables, it has to be assumed that they represent bivariate data. All bivariate data commands accept a list of data points as an argument in place of two lists of numbers. In a perfectly natural way, wiris takes the abscissae of the points as the values of the first variable and the ordinates as the values of the second variable observed in the elements of the sample.
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