1. Topic: Problem with Sampling Reading: Baker, Stephen (2009)
Topic: Problem with Sampling Reading: Baker, Stephen (2009). They’ve Got Your Number: Data, Digits and Destiny - how the Numerati are changing our Lives. (Chap 7, Lover) Group 5: Shu Min, Yan Ling (Presenter), Yi Mou

2. Outline Online dating story
Problem with sampling – small sample, not randomized, credibility of results from questionnaire
Cell phone experiment
Problem with sampling – voluntary sample, not randomized
Conclusion

3. Online dating story
Reveal the algorithms of love through an online dating service- Chemistry.com
Author and his wife will describe the characteristics of one another as their ideal partner

4. Questionnaire Personal details
Ideal partner one is willing to consider
Personality
Essay to describe oneself
Length of index and ring fingers

5. Involuntary data not available to user
Record the clicks, measure which types of potential dates appear to interest the user the most
Study the behavior, observe trends, recommend ppl that are similar to the user

6. Hormones <-> Personality
Science-based matching algorithm designed by Helen Fisher
Fisher’s theory is that 4 different hormones mold our personalities
Director (Testosterone), Negotiator (Estrogen), Builder (Serotonin) and Explorer (Dopamine)

7. Outcome
Compatibility is matched on various attributes - personality groupings, cultural, educational level etc
The algorithms have completed their work – Both are a match to each other.

8. Problem with sampling Small sample Not randomized
Credibility of results from questionnaire

9. Cell phone experiment
Objective: Observe similar patterns between different profiles of people
Experimenter: Nathan Eagle, a PhD student at MIT’s Media Lab
Methodology: Distributed cell phones to 100 graduate students (25 business, 75 engineering students). Phones were equipped with software to record the movements and interactions of people
Duration: 1 year

10. Outcome
Nathan Eagle observed that the 2 groups of subjects had different lifestyle patterns
Build models of the individuals
Each person’s life was very predictable

11. Problem with sampling
Not random
Voluntary sample

12. Conclusion Representative sample
Underlying distribution of the population
Randomization
Size of sample
Type of sampling methods

13. Thank you!