"Lies, damned lies, and statistics" is a popular phrase that is often used to disparage statistics that do not properly support a particular position. Humans have a fondness for numbers, but unfortunately those numbers are sometimes misused or even abused.

1. Debashish Jana

2. The term was popularised in United States by Mark Twain (among
others), who attributed it to the British Prime Minister Benjamin
Disraeli:
"There are three kinds of lies:
lies, damned lies, and statistics."

5. "Lies, damned lies, and statistics" is a phrase describing the persuasive
power of numbers, particularly the use of statistics to bolster weak
arguments. It is also sometimes colloquially used to doubt statistics
used to prove an opponent's point.

6. A misuse of statistics is a pattern
of unsound statistical analysis.
They are variously related to data
quality, statistical methods and
interpretations. Statistics are
occasionally misused to persuade,
influence and sell.

7. Apples and Oranges is a common term to describe an attempted
comparison between things that can't be fairly compared. The term can
also describe a false analogy.
“Consider a comparison of a human to a mobile phone based on how
many numbers each can add per second.”

9. Cognitive biases are patterns of thought that lead to suboptimal
outcomes such as poor decisions. Most are the result of mental
shortcuts, logical errors, social factors and memory shortfalls.

11. Data dredging is the automated
statistical analysis of large sets of
data.
It is similar to data mining with
the key difference being that data
mining starts with a hypothesis, or
something that you expect to find
in the data. Data dredging is an
automated search for statistical
patterns that doesn't start with a
hypothesis.

12. Garbage in, garbage out is a rule of thumb that fights the common
temptation to view technology as magic that can always produce
results. Specifically, it is common for people to believe that technology
can predict the future or optimize results based on data without
thinking about the nature of the data or the problem at hand.