Abstract
If we want to analyze a real system with a large number of input data, it is very convenient to determine a probability distribution that best fits to given input data. There are many statistical methods to determine the correct probability distribution and one of them is Chi-Square Goodness of Fit Test. This statistical test can be also used to find out a probability distribution of time intervals between arrivals of customers at post office. Intervals between arrivals of customers occur in continuous time and therefore we consider continuous probable distributions.
Highlights
In real systems such as queuing systems at post offices are based on random events
The first characterization of the exponential distribution was elaborated by Ghurey (1960) and Teicher (1961) which modified the characterization of normal distribution to the exponential distribution
In the order to examine the properties of the system at post Office in Bytča we made 7 measurements of customer input
Summary
In real systems such as queuing systems at post offices are based on random events. A system is a set of elements that are arranged in a certain way. The result of random event is a random variable [10, 12]. Discrete random variables are usually integer values. Continuous random variables are values from closed or non-closed interval. When we examine a particular system, we work with a number of data that represent the values of a random variable. In this case, it is advantageous to determine laws of probability that are attached to the given data. One of them is a probability distribution that describes the probability of the random variable in each value. Probability distribution is the probability of occurrence of each outcome and in the context of queuing system at post office the outcome represents the event - the customer's arrival at the post office
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