Statistical bias and insufficiency!

Please visit my web page "Urban Tenets" at https://urbantenets.nl/

************************************************

The problem with statistics other than it's 1) susceptibility to misinterpretation and 2) confirmation bias is that 3) the moment you try to universalise statistical outcome, it gets diluted and loses its granularity and significance and 4) if you hardly get any robust and substantiated temporal data of a specific region or set of subjects (with its innate challenges, strengths, context and conditions) to support your argument it anyway still remains too remote, meagre or ephemeral to be of any material significance to the other three fourth part of world.

e.g., wrt above numbers

1) #Commercial / #political interest statistics

2) #Agenda / #ideological driven statistics

3) encompassing subjects like #poverty #urbanisation

4) statistics wrt #ecology, #heritage, #bicycleusage

If not true for all sectors, segments or subjects; same has been recurring  theme and daunting issue with majority instances of statistical interpretation/ outcome

Statistics to be presented with a note of caution and to be received with a dash of scepticism.

Author: Anoop Jha

#Statistics  #modeling #projection #urbanplanning #governance #commerce