Analysis of ted talk, lies, damned lies and statistics by sebastian wernicke
1. Analysis of ted talk, Lies,
Damned Lies and Statistics by
Sebastian Wernicke
By Darpanraj Deoghare
2. Who is he?
Currently an Engagement
Manager at Oliver Wyman,
Sebastian Wernicke originally
studied bioinformatics at
Friedrich-Schiller-Universität Jena.
During his time in academia, he
devised an algorithm for analyzing
biological networks that now aids
researchers in dealing with their
innate complexity.
9. Relevance No 1
Topic
Sebastian first looked at the list of top
ten words that make a successful talk
and an unsuccessful talk.
For example if you came to TED to talk
about how French coffee will spread
happiness in our brains than it will be a
successful talk. Whereas, if you wanted
to talk about your project involving
oxygen, girls, aircraft than the statistics
say the talk would not be successful.
10. Relevance No 2
Conducting Complex Analysis
Conduct & Study complex
analyses
Identify the market trends
Collect data on customer needs
Develop plans to target the
demanding service
Implement required business
process
11.
12. Relevance No 2
Delivery
Most Favourite talks = 50% + Least Favourite talks
This is true for most of the cases
13. Summary
Wernicke looked at a statistical model to see if the was a
way to make a really good, or a really bad Ted talk. What
three things did he look at?
He gives the example of four things that are good to talk
about, and four things that are not so good. What are his
examples?
Ted talks that are long are more, or less, popular than short
ones?
At a conference in most disciplines it would never do to say
“etcetera, etcetera.” What does Wernicke say about that in
Ted talks?
What does he say about appearance on stage?
Although Wernicke uses humor in this talk, in the overall
message what is he implying about evaluating talks by
popularity?