The Rio Tinto Minerals (RTM) facility in Boron California is experiencing a sack of revenue. In the past 18 calendar months the RTM has sustained a dearth of an estimated $1,754,000.After a complete analysis into the last 18 months of drudgery issues, the problem became perceivable to be a unprocessed ore and immature equipment failure. Further investigation concluded the plants (BAP) belt conveyor scheme accounted for the bulk of the equipment failure. Hence, resulting in approximately 15 % of loss clutch tons per month in which 1 % discount be directly related. The following result illustrate and analyze the profound tendency and dispersion measures calculated using the data collected. We will formulate these calculations using the Gauss curve. The Gauss curve is one of the most everyday dispersal function, especially in error theory. It can be traced back to 1733 in which the English-French mathematician de Moivre worked on the curve. The Gaussian distribution can be proved that each measurement is the result of a large amount of small, independent error sources. The Gaussian distribution is also commonly called the normal distribution and is often exposit as a bell-shaped curve. (Gauss curve, 2004)
Examining the data further, the troika central tendency measures the mean, median, and mode can all be identified.
The mean is the sum of all the muzzy tons put down divided by the total number of the events. During the 18 month period, 29 events totaling 4,953 lost tons were identified. The calculated mean for the events is 151.2 lost tons per event. The median is determined by choosing the center in the progression of the events. If the total event number is odd, the middle treasure is the median. If the total event number is even, the two values in the middle are added to subscribe toher and divided by...
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