1. Introduction to Business
Statistics
Emergence of Data Driven Decision Making, Use cases,
Drawing Insights
“In God we trust, all others must bring data”
- W Edwards Deming
Dr. Indranil Ghosh, IT & Analytics Area, Institute of Management Technology,
Hyderabad, Telangana, India
2. “If the statistics are boring, then you’ve got the
wrong numbers” – Edward R. Tufte
3. “The Purpose of Visualization is Insight – Not
Pictures” – Ben Shneiderman
4. Implications
• There will be more traffic to online dating sites during December/January.
• There will be greater demand for relationship counsellors and lawyers.
• There will be greater demand for housing and the housing prices are likely to
increase in December/January.
• There will be greater demand for household items.
5. Insights Beyond Insights
• Correlated with Facebook relationship breakups, divorces spike in January.
According to Caroline Kent (2015), January 3 is nicknamed as ‘Divorce Day’.
• People would like to forget the past, so they might change the brand of beer
they drink.
6. “If you torture the data long, it will confess”-
Ronald Coase
• RadioShack and Best Buy found a high correlation between success of
individual stores and number of female employees in sales team (Underhill,
2009)
• In 2014, China Eastern Airline found that a man had booked a first class
ticket more than 300 times in a year and cancelled it before its expiry for full
refund so that he could eat free food at the airport’s VIP lounge (David K Li,
2014)
7. London Cholera Outbreak - 1854
Severe outbreak of cholera that occurred near
Broad Street (now Broadwick street) in Soho
district of London in 1854.
More than 500 people died within 10 days of the
outbreak, the mortality rate in some parts of the
city was as high as 12.8%.
8.
9.
10. What is Statistics?
• “There are three kinds of lies: lies, damned lies, and statistics” – Mark Twain
• “It is easy to lie with statistics, it is easier to lie without them”- Frederick
Mosteller
• Statistics is about summarizing data and to infer
• Loss of Information Granularity
11. Walkthrough ‘statistia’
• The word statistics means different things to different people.
• To a football fan, statistics are rushing, passing and first down numbers. To FDA,
statistics is the likelihood of undesirable effects in the general population using the
new prostate drug etc.
• Each of these people using statistics correctly, yet each person uses it in a different
way.
• The word statistik comes from Italian word statistia which means "statesman".
• First used by Gottfried Achenwall (1719–72).
• Long before the 18th century, people had been recording and using data.
12. What is Business Statistics
• Business statistics provides a formal basis to:
• Summarize and visualize business data
• Reach conclusions from business data
• Make reliable predictions about business activities
• Improve business processes
13. Leveraging Business Statistics
• Can we predict whether a song will be a hit or not? (Apparently, Polyphonic HMI
launched a product ‘Hit Song Science’ to accomplish that (Anon, 2013))
• Can we recommend movies to the customers? (Netflix thrives on it (MacKinzie et
al., 2013))
• Can we predict who is likely to leave the company? (Hewlett Packard developed a
flight risk score for its employees to predict the same (Siegel et al., 2013)).
• Can dream foresee whether one’s spouse will cheat? (University of Maryland
claimed so (perhaps in their dream!!!) (Whitelocks, 2013)
14. The Way Forward
The emerging field of Business Analytics combines methods from:
• Statistics (exploring & analyzing data).
• Information systems (collecting & processing data).
• Management science (optimization models).
to support fact-based decision making.
28. What we are going to traverse
• Introduction to Fundamental Statistics, Descriptive Analysis, Data
Visualization
• Inferential Statistics
• Measures of Association, Naïve Predictive Modeling
• Hands on with Statistical Packages (Blue Sky Statistics/Power BI)
• How to make decisions
29. References
• Anon (2003), “Major Music Labels Use Artificial Intelligence to help determine Hitability of
Music”, Music Industry News Network, 25 February 2003.
• MacKenzie I, Meyer C, and Noble S (2013), “How Retailers can keep up with Customers”,
McKinsey & Company Insights, October 2013. Available at
http://www.mckinsey.com/industries/retail/our-insights/how-retailers-cankeep-up-with-
consumers accessed on 20 March 201
• Siegel E (2013), “Predictive Analytics: The Power to Predict who will Click, Buy, Lie or
Die”, John Wiley and Sons, Hoboken, NJ.
• Whitelocks S (2013), “Having nightmares about your husband cheating? It may might be
true. New research finds Dream can predict future relationship behaviour”, Daily Mail, 16
May 2013.
