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How to spot a bad
statistic
Based on the TED talk ‘3 ways to spot a bad
statistic’
by Mona Chalabi
2 Key Takeaways
1.
Being mindful of underlying
uncertainties behind any statistic
avoids overvaluing the figure
For instance the probability of a Clinton win in
the recently concluded US elections was
reported till double decimal places
With a population of 230 million and such
diversity, it is nearly impossible to cover a
sample that is a true representative of the
population, let alone predict the number till 2
decimals
These overstated statistics do even more
damage when reported using suave visuals as
they morph the idea of any fallacy
The concept of ‘average’ numbers should be
perceived with even more caution since they
tend to over generalize metrics
2.
An added knowledge of the data
source used to calculated a
statistic brings in more realism to
its value
For instance, one poll found that 41 percent of
Muslims in the US support jihad, which is
obviously pretty scary
But, it turns out only 16 percent defined it as,
"violent holy war against unbelievers.“. It is
also possible that no one in the survey who
defined it as violent holy war also said they
support it.
And finally, only 600 respondents took part in
that poll. There are roughly three million
Muslims in this country, according to Pew
Research Center. That means the poll spoke to
roughly one in every 5,000 Muslims in this
country which in no way is an accurate sample
While collaborating with Analysts, Managers
need to be aware of these caveats as a false
statistic can drastically change the course of
any analysis and its reporting
Thank You
Disclaimer:
This presentation was created by Raminder
Singh, under an internship by Prof. Mathur,
IIM Lucknow

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3 ways to spot a bad statistic

  • 1. How to spot a bad statistic
  • 2. Based on the TED talk ‘3 ways to spot a bad statistic’ by Mona Chalabi
  • 4. 1. Being mindful of underlying uncertainties behind any statistic avoids overvaluing the figure
  • 5. For instance the probability of a Clinton win in the recently concluded US elections was reported till double decimal places
  • 6. With a population of 230 million and such diversity, it is nearly impossible to cover a sample that is a true representative of the population, let alone predict the number till 2 decimals
  • 7. These overstated statistics do even more damage when reported using suave visuals as they morph the idea of any fallacy
  • 8. The concept of ‘average’ numbers should be perceived with even more caution since they tend to over generalize metrics
  • 9. 2. An added knowledge of the data source used to calculated a statistic brings in more realism to its value
  • 10. For instance, one poll found that 41 percent of Muslims in the US support jihad, which is obviously pretty scary
  • 11. But, it turns out only 16 percent defined it as, "violent holy war against unbelievers.“. It is also possible that no one in the survey who defined it as violent holy war also said they support it.
  • 12. And finally, only 600 respondents took part in that poll. There are roughly three million Muslims in this country, according to Pew Research Center. That means the poll spoke to roughly one in every 5,000 Muslims in this country which in no way is an accurate sample
  • 13. While collaborating with Analysts, Managers need to be aware of these caveats as a false statistic can drastically change the course of any analysis and its reporting
  • 14. Thank You Disclaimer: This presentation was created by Raminder Singh, under an internship by Prof. Mathur, IIM Lucknow