{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

lecture6 - Data Mining CS57300 Purdue University Decision...

Info icon This preview shows pages 1–8. Sign up to view the full content.

View Full Document Right Arrow Icon
Data Mining CS57300 Purdue University September 14, 2010
Image of page 1

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Decision making
Image of page 2
Heuristics and biases Tversky & Kahneman, psychologists, propose that people often do not follow rules of probability Instead, decision making may be based on heuristics Lowers cognitive load but may lead to systematic errors and biases • Examples: Availability heuristic Representativeness heuristic Confirmation bias Conjunction fallacy Numerosity heuristic
Image of page 3

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Estimating probabilities (Tversky & Kahneman ’73/’74) Question: Is the letter R more likely to be the 1st or 3rd letter in English words? Results: Most said R more probable as 1st letter Reality: R appears much more often as the 3rd letter, but easier to think of words where R is the 1st letter
Image of page 4
Estimating probabilities (cont) Question: Which causes more deaths in developed countries? (a) traffic accidents or (b) stomach cancer Typical guess: traffic accident = 4X stomach cancer Actual: 45,000 traffic, 95,000 stomach cancer deaths in US Ratio of newspaper reports on each subject: 137 (traffic fatality) to 1 (stomach cancer death) Availability heuristic : Tendency for people to make judgments of frequency on basis of how easily examples come to mind
Image of page 5

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Base Rate Study (Kahneman & Tversky '73) Participants told that for a set of 100 people are either: 30% engineers/70% lawyers, or 70% engineers/30% lawyers Given: A description of a person Jack, which is representative of a prototypical engineer (e.g., likes carpentry and mathematical puzzles, careful, conservative) Question: Is Jack more likely to be a lawyer or engineer? Results: Participants in the 30% condition judged Jack just as likely to be an engineer as participants in the 70% condition.
Image of page 6
Base rate study (cont) People use the representative heuristic to make inferences... Inferences is based solely on similarity of target to category members Base rates (70%-30%) are ignored ...rather than using formal statistical rules to make inferences Inferences should be based on similarity of target to category members AND base rates (70%-30%) Representative heuristic : categorizations made on the basis of similarity between instance and category members
Image of page 7

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Image of page 8
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

What students are saying

  • Left Quote Icon

    As a current student on this bumpy collegiate pathway, I stumbled upon Course Hero, where I can find study resources for nearly all my courses, get online help from tutors 24/7, and even share my old projects, papers, and lecture notes with other students.

    Student Picture

    Kiran Temple University Fox School of Business ‘17, Course Hero Intern

  • Left Quote Icon

    I cannot even describe how much Course Hero helped me this summer. It’s truly become something I can always rely on and help me. In the end, I was not only able to survive summer classes, but I was able to thrive thanks to Course Hero.

    Student Picture

    Dana University of Pennsylvania ‘17, Course Hero Intern

  • Left Quote Icon

    The ability to access any university’s resources through Course Hero proved invaluable in my case. I was behind on Tulane coursework and actually used UCLA’s materials to help me move forward and get everything together on time.

    Student Picture

    Jill Tulane University ‘16, Course Hero Intern