Quantifying accuracy and precision:
Ideally a measurement device is both accurate and precise, with measurements all close to and tightly clustered around the known value. The accuracy and precision of a measurement process is usually established by repeatedly measuring some traceable reference standard.
Precision is usually characterised in terms of the standard deviation of the measurements, sometimes called the measurement process's standard error. The interval defined by the standard deviation is the 68.3% ("one sigma") confidence interval of the measurements.
If enough measurements have been made to accurately estimate the standard deviation of the process, and if the measurement process produces normally distributed errors, then it is likely that 68.3% of the time, the true value of the measured property will lie within one standard deviation, 95.4% of the time it will lie within two standard deviations, and 99.7% of the time it will lie within three standard deviations of the measured value.
This also applies when measurements are repeated and averaged. In that case, the term standard error is properly applied: the precision of the average is equal to the known standard deviation of the process divided by the square root of the number of measurements averaged. Further, the central limit theorem shows that the probability distribution of the averaged measurements will be closer to a normal distribution than that of individual measurements.(This is where i am emphasizing all future datas ,even Random,
can be Measured in Pobability distribution & i am seriously considering to use
Price & Volume in "X" axis together to find the Right / Left bias ,when viewed
putting intraday charts Time axis not on conventional form as presented by all s/w,plz suggest if any kind of trading software does that)
With regard to accuracy we can distinguish:
the difference between the mean of the measurements and the reference value, the bias.
Establishing and correcting for bias is necessary for calibration.
the combined effect of that and precision
A common convention in science and engineering is to express accuracy and/or precision implicitly by means of significant figures. Here, when not explicitly stated, the margin of error is understood to be one-half the value of the last significant place.
Plz note the Cache here:
However, reliance on this convention can lead to false precision errors when accepting data from sources that do not obey it.(Here datas stationary & non-stationary status & quality disturbed me).
Precision is sometimes stratified into:
Repeatability - the variation arising when all efforts are made to keep conditions constant by using the same instrument and operator, and repeating during a short time period; (Our forum's MACD / Pattern specialists / etc ; "et all' steps here)
Reproducibility - the variation arising using the same measurement process among different instruments and operators, and over longer time periods.
(Self Stress ,bias,comfort zone,varies with individuals)
A common way to statistically measure precision is a Six Sigma tool .
As stated before, you can be both accurate and precise. For instance, if all your arrows hit the bull's eye of the target, they are all both near the "true value" (accurate) and near one another (precise).
This is why all trader's are inclined to "System based Trading" we can try to be both accurate & precise.
Asish
