Way of expressing precision measurement

With application of statistics to scientific problem, it has permitted scientist to reject or accept conclusions on the outcome of analysis figures depending on the degree of precision or attached numerical report.

Precision can be define as the point of agreement between replicate measurements of the same quantity.

In term of precision expression there various available tool that are used. Some of the tools are: average deviation, variance, standard deviation etc.

Average Deviation

This tools is used to show dispersion or to make sure that the deviation from the center of the values. It also known as Mean Deviation. It further assist in measuring distribution that depend on the items in the distribution.

The mean deviation has following formula;

A.D = Σ| x – | or Σ|d|

n n

dx = deviation from mean

x = observation

= sample means

n number of observation

Mean deviation coefficient = Mean deviation

Mean

In compliance with high value, precision measurement, for example average deviation may be illustrated as an absolute figure or as relative of (%, pph, ppt, etc).

Variance

Variance is simple refer to square deviation. Variance is very significant method of measuring quantitative analysis of data. Variance assist in determine the effect of different factors. It also assist in generating some statistical theories.

Below is the formula use to find the variance;

Variance S² = Σ(x – )² or Σ(d)²

————– —————-

n – 1 n – 1

x = arithmetic means

n= number of observation

Standard Deviation

It is the most often method of measuring dispersion. The measure how closely the data are clustered about the mean.

Point to know is that smaller standard deviation give more closely clustered data about the means i.e homogeneity is observed when standard deviation so small.

As such standard deviation measure the observation in a spread set.

Standard deviation is simply the square root of the variance.

S = Σ(x – )² or Σ(d)²

————– —————-

n – 1 n – 1