The discrete random variable is a variable that takes only discrete values, e.g. 1, 2, 5, etc. If we plot a graph with the discrete variables, it is a dotted graph, where each dot represents a value. The peculiarity of the discrete variables is that it is impossible to obtain a variable value between the two nearly dots (Anderson, Sweeney & Williams, 2001). In a restaurant business, there are several examples of discrete random variables. These are the daily number of customers, the number of free, engaged or booked tables, the number of dishes served. However, if the manager needs to calculate the central tendency of the discrete variable, the median or mode should be used. The weekly or monthly mean of any variable can be fractional, e.g. 6.5, or 4.25, and it is not always accurate to use the fractional number for the discrete variable (Anderson, Sweeney & Williams, 2001). Therefore, the manager has to be aware of this fact.
The continuous random variable is a variable that can take any value within a certain range, e.g. from 0 to infinity. When a graph with the continuous variable is plotted, the data values are represented with dots united with a line. Therefore, the variable can take any value between the two neighboring values (Anderson, Sweeney & Williams, 2001). The prices of the dishes, the energy value of the dish, the quantity of the electricity consumed, the customers’ bills are the examples of the continuous random variables. Their values are often represented as fractional numbers, and the best measure of the central tendency is mean (Anderson, Sweeney & Williams, 2005).
The Poisson distribution is used to present the discrete random variables. The continuous random variables are characterized either with the normal distribution or with Student’s t-distribution (Anderson, Sweeney & Williams, 2001).
References
Anderson, D. R., Sweeney, D. J., & Williams, T. A. (2001). Quantitative methods for business. Cincinnati, OH: South-Western College Pub.
Anderson, D. R., Sweeney, D. J., & Williams, T. A. (2005). Statistics for business and economics. Mason, Ohio: Thomson/South-Western.
