|Teach me something I don't already know !
Scenario A: You attend a conference on financial performance of the hedge funds industry. The CEO of a fund of funds reports that the annual mean return of his funds is 5.4%, and the median return was 6.1%. The CEO adds that: “We are especially proud to report that all funds did not differ much in their performance as it is expressed in a historical low standard deviation of return of 0.6%”.
Scenario B: In his annual address, the Chairman of the Board of a large trading company introduced his philosophy on reward and penalty. He said: "Unlike what classical theories suggest, I found reward and penalty not equally efficient. Penalty is indeed efficient while rewarding acts almost the opposite way". To support his claim, the chairman brought some data on top-level traders and on failing traders within his company. A majority of the top-traders from last year who were praised for their performance showed a lower performance this year. On the other hand most of the failing traders of last year who were reprimanded showed a better performance this year.
Chances are (statistically speaking) that if you only had "college statistics," you would not know WHY at least one of the two above-mentioned scenarios are statistically problematic.
While basic and familiar issues in statistical theory regarding description and inference will still be covered, we will use this graduate-level course to deepen the understanding of statistics so as to make you a much better consumer (and manufacturer) of statistics. Challenging statistical issues, not covered by most text books, will be addressed using real-life quantitative examples from the business world.
The mode of teaching emphasizes understanding over memorizing.
Teaming up: Students are required to form working teams of up to 5 students per team. Homework assignments are handed-in as one hard copy per team that includes names of all team members.