Question

Too often, statistics are used to ‘prove’ some point or to persuade an audience to some particular point of view, without really being accurate, complete, or honest. This issue has been the subject of numerous texts. You may be interested in reading such titles as Damned Lies and Statistics, or How to Lie with Statistics. Explain why the use of analytics contributed to the problem. Discuss the consequences of the matter. Did the company/organization involve suffer any adverse consequences?

Answer 1

Statistics:

• When working along with statistics and certain analysis of the data accuracy and efficiency is one of the most important things which needs to be checked or else there can be many problems which will make the organization suffer later due to the wrong predictions.
• Many of the organizations use such data analysis techniques to acquire their target audience but if the statistics are not being calculated accordingly it makes too many losses for the organization in terms of the research and development of the organization.
• There can be many consequences of false analysis done. Some of them are as follows:
  • The first and most important thing that will have an impact here is that the target audience would be a wrong audience if any calculations go wrong which will make a lot of loss for the company as they will be investing in the wrong audience which will let their sales go down and many such things can happen following it.
  • Also, the company will gather the wrong data from the analysis and if the analysis is not done properly than the data gathered will be of no use. Hence, the resources that were invested in this research would be going in vain.
  • As we know that statistics can add an impact on the users it can be the major driver in spreading wrong data to the audience which will refer to dispersing false data that will impact the users by spreading wrong knowledge.
• If we look in a way all these consequences are adverse but if we talk about the company/organization then yes it can be adverse as the investment in such projects can go to vain if there is even a slight of mistake in the calculation of the aspects.

Hence, these are the consequences of data analysis or statistics with the help of the R&D team.