The normal distribution is a continuous probability distribution, which is used to characterize a wide variety of types of data. It is a symmetric distribution and is completely determined by its mean and standard deviation. The normal distribution is particularly important in statistics because of the tendency for sample means to follow the normal distribution.
The figure hereafter is a representation of the frequency distribution of a large set of values obtained by measuring a single control material. This distribution shows the shape of a normal curve. Note that a "gate" consisting of ±1 σ accounts for 68% of the distribution or 68% of the area under the curve, ±2 σ accounts for 95% and ±3 σ accounts for >99%. At ±2 σ, 95% of the distribution is inside the "gates," 2.5% of the distribution is in the lower or left tail, and the same amount (2.5%) is present in the upper tail. This curve is like an error curve that illustrates that small errors from the mean value occur more frequently than large ones.
Figure D3 – Gaussian distribution law
The normal distribution is also known as the Gaussian distribution after its inceptor, Johann Carl Fredirich Gauss.
2.5.7. Confidence interval
A confidence interval is a statistic constructed from a set of data to provide an interval estimate for a parameter. For example, when estimating the mean value of a normal distribution, the sample average provides a point particular estimate or best guess about the value of the mean. However, this estimate is almost surely not exactly the correct physical value. A confidence interval provides a range of values around that estimate to show how precise the estimate is. The confidence level associated with the interval, usually 90%, 95%, or 99%, is the percentage of times in repeated sampling that the intervals will contain the true value of the unknown parameter.
Confidence intervals rely on results from the normal distribution.
Flight Operations & Line Assistance Getting to Grips with Aircraft Performance Monitoring
CRUISE PERFORMANCE ANALYSIS
2.6. The APM archiving system
The APM program enables the storage of aircraft performance data in libraries for long term trend monitoring. Both input data coming from measurements and output data issued from the analysis can be stored in libraries. This feature enables to monitor the aircraft degradation trend with time so
as to identify any corrective actions to be taken. It also enables to obtain average
results over all the tail numbers of the fleet.
A nice-handling interface provides an efficient and proper data management via
these so-called APM libraries.
2.7. Some nice-to-knows about the APM
To determine the aircraft performance level with accuracy, a certain number of parameters must be recorded prior to take off and in-flight.
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