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Statistica Corrente (Current Statistics)
Title:Statistica Corrente (Current Statistics)
Category:Utility/Scientific
Release Date:
Language:Italian
Size:16K
Machine:PAL & NTSC
Code Type:Basic
Distribution:Type-in
Published by:J.Soft
Notes:Written by (private). Typed in by saver71.
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Statistica Corrente Title Screenshot

Statistica Corrente Screenshot


Publications
Published: Papersoft 31/1985 (Magazine/Italian) pg. 12


Description
This program allows you to obtain the fundamental statistical parameters from any set of numerical data. The first thing that needs to be entered is the number of data to be processed (up to 500); after which the values ​​are entered, which takes place in groups of 15. After setting each group, it is necessary to confirm the accuracy of the data on the computer; if one or more errors have been made, the possibility of making corrections is given. After a processing time that depends on the number of data, varying from a few seconds to a few minutes, the results are displayed, namely:
- the sum and the arithmetic mean (average value) of the data;
- the highest value, the lowest value and their difference, called variation;
- the median, that is the value that divides the data in increasing order in half;
- the standard deviation, which is the measure of how much the data deviate on average from the mean value.

The standard deviation therefore allows an evaluation of the dispersion of the data, that is, of how much they are "scattered" with respect to the average value. In particular, by adding and subtracting the standard deviation from the arithmetic mean, we obtain the extremes of an interval which, if any, includes 68% of the data. The existence of this interval is subject to the fact that the sum of the average value and the standard deviation does not exceed the maximum value, and their difference is not less than the minimum value. If these conditions are met, the program displays the extremes of the interval. The most reliable results are obtained if the distribution of the data is of the "Guassian" type, that is, if the majority of the values ​​are concentrated around the arithmetic mean. Let's take an example to clarify the ideas: if you try to weigh several apparently identical packages of the same product with a precision balance, the measurements will generally be different but will form a Gaussian distribution. In this case, the program allows you to evaluate how carefully the quantity of product sold is determined.

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