Globally every human being has phases of life, in a similar pattern technology, invention, discoveries, research, society, nature have phases. If we begin with an human beings, at one point of time everybody would have come across the life of a student. During our graduation days, myself, yourself or take the case of anybody i could definitely say most of us scolded for the theories, discoveries, inventions and history which we were learning in our graduation for our examinations.
Probably we would have gone to extent by cursing the person who discovered the theory , simply we would have quoted to our friends " if he is alive and if i see the person who created these theories , that's it he is gone ". These could be due to any kind of reasons, jokes apart here i am not trying to figure the reasons why, when , what and where, but i wish to rewind to the past and come to the present.
Statistics is a simple 10 letter word but if i get into the world of theories to find out how this word is contextually used, it is astonishing and surprising. If we could just rewind our picture to 18th century, statistics means systematic collection of demographic and economics data. Now when we move forward to 19th century, the meaning has been broadened which is an inclusive of collection, summary and analysis of data. Moving forward to 21st century, with the advent of computers, computation of statistics transformed to be simpler version.
There were many statistical concepts which has a impact with a wide range of sciences especially in probability and design of experiments. Of course, in this modern era several statistical methods like regression approach, predictive modelling, survival analysis, bayesian analysis, time series, data mining, multivariate techniques, reliability analysis, quality control are widely applied in almost most fields. However, big data analytics is considered to be a big boom in this world of statistics with the evolution of modern computers and technologies.
Even though most of us would be aware of the history of big data analytics , if not, there was an blog by Bernard Marr which you could check out using our buddy Google. Large data centers came into existence in the year 1965 and the world of analytics empowers in almost several fields especially the data scientist ( most common word in Linkedin) who handles terabytes ,gigabytes of data in an single day faces several challenges. Big data can be seen in Finance and other business services especially when it comes in the application of stock exchange.
But, without no scientific knowledge on statistics one cannot become as complete data scientist. Machine learning algorithms autonomously analyses the data which is fed into the system with support of various software , identifies the patterns of the data and also visualises the result. To handle such a huge data i could agree computational knowledge is important, but theoretical knowledge about statistics is much more important . As already quoted, theory without knowledge will not lead into a good statistician. Before any analysis definitely thorough scrutiny and understanding of the data is must. Let the data be of any kind, but what kind of statistical tools and measure is an high priority. With any wrong statistical methods implied on the data will lead to an fallacious conclusions. At no point of time, result should never be biased and changed towards the favor of the objective. Data should speak itself with the support of statistics.
So let us wait and see for further stages of statistics.
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