https://www.ted.com/talks/sebastian_wernicke_how_to_use_data_to_make_a_hit_tv_sh
ID: 3370313 • Letter: H
Question
https://www.ted.com/talks/sebastian_wernicke_how_to_use_data_to_make_a_hit_tv_show Watch the Ted Talk "How to Use Data to Make a Hit TV Show" by Sebastian Wernicke and answer the following questions: How can you understand and explain the Netflix and Google exmaples using the statistical concepts of regression and correlation? In other words, describe the processes described in the Ted Talk using statistical concepts and terms. Why were the predictions made not perfect, statistically speaking? In what other real-world examples would regression and correlation prove beneficial? What cautions/concerns should business/people make when interpreting correlational and predictive results?
Explanation / Answer
From Ted talk, Statistics theory falls into two camps, frequentist and Bayesian. Frequentist is older and solid. Bayesian is newer, more flexible, and more exciting. In particular, there are the exciting things that can be done with Markov Chain Monte Carlo and related techniques.
He explains,
predicting the future is not a theoretical superpower, it’s part of the job. But our approach to prediction seems stuck in the past. Most business forecasts fail to include measurable outcomes and are not recorded, so it is hard to know if we are even getting better at them.
In students taking maths and enflish test, we could use correlation to determine whether students who are good at maths tends to be good at english as well reggression to determine whether the marks in english can be predicted for given marks in maths . in this field regression and correlation prove beneficial.
The resulting statistic you get from a correlation equation is called a correlation coefficient. There will always be two parts to a correlation coefficient. First part is the coefficient is a positive number or a negative number. second part is The number will always be between zero and one. That means that the correlation coefficient will always be somewhere between negative one and positive one, but it could be anywhere in between.
Related Questions
Navigate
Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.