The power of Averages,
it means a lot
if you can
understand Means, a lot.

Assuming a Normal Distribution,

A Standard Deviation, or σ
defines where about 68% of the data falls;
roughly 34% above and below the Mean.

Two Standard Deviations
defines where a further 28% of data lies;
14% above and below 1σ and -1σ.

Positive 1-Sigma is one Standard Deviation above the Mean
Negative 1-Sigma is one below;
The range from -2σ to 2σ includes  96% of data.
The implications are astounding.

Within 3 Standard Deviations, one finds 99.7% of the data;
Within 4σ, 99.9%, 5σ, 99.999%,
the remainder are generally outliers and other improbable results.

To illustrate:

Suppose we had a group of 100 people,
and we wish to determine average height:
If our Mean height ends up being, say, 180 cm,
with a Standard Deviation of 20cm,
We can suppose that of 100 people, on average,
with a certain Margin of Error that is inversely proportionate to our Sample Size, or n
(for sake of argument, the Probable Error, or γ, is 13.49cm)

4 are taller than 220cm
14 are between 200cm and 220cm
68 are between 160cm and 200cm
14 are from 140cm to 160cm
4 are shorter than 140cm
--

Statistics is the parent of Probability;
Statistics is the Art and Science of Forecast,
Statistics paves the way for modern Science
Statistics is a powerful weapon in the fight against Ignorance
Statistics, however, are generally and intentionally misrepresented and thus misunderstood.

For increasingly accurate figures,
one must have a larger Sample Size
and a Sample group that is a representative subgroup
of the Whole

This is intentionally abused
by most of the News
you read or see each day on Paper and Screens alike.

If a "Statistical analysis" does not include at least
Margin of Error or Probable Error,
Mean (Average), Standard Deviation, and Sample Size
do not take it as accurate.

Depending on the source,
it could even be deliberately malicious.

Arm yourself with Knowledge.