by clicking on the page. A slider will appear, allowing you to adjust your zoom level. Return to the original size by clicking on the page again.
the page around when zoomed in by dragging it.
the zoom using the slider on the top right.
by clicking on the zoomed-in page.
by entering text in the search field and click on "In This Issue" or "All Issues" to search the current issue or the archive of back issues respectively.
by clicking on thumbnails to select pages, and then press the print button.
this publication and page.
displays a table of sections with thumbnails and descriptions.
displays thumbnails of every page in the issue. Click on a page to jump.
allows you to browse through every available issue.
FCW : March 15, 2014
Bookshelf Models, models everywhere The insight that even simple models can lead to surprisingly accurate decisions has been around for some time. In 1954, Paul Meehl, a psychologist at the University of Minnesota, compared expert forecasts with the predictions of simple statistical models. Although the models used only a fraction of the data available to the experts, they were almost always more accurate. A number of similar studies have reached the same conclusion. Even seemingly crude models often do very well. Models are accurate in part because they avoid common errors that plague humans. People suffer from the recency bias, placing too much weight on recent information while downplaying earlier data. They pay too much attention to information that is readily a They re also unreliable: Giv someone the same informat on two different occasions, he or she may reach two rat different decisions. Models have none of these problem They can also crunch copio amounts of data accurately reliably. For decades decision models have made importan contributions to a wide variety of elds. Colleges rely on models to evaluate applications for admission. By using formulas that assign weights to variables --- high school grade point average, test scores, recommendations and extracurricular activities --- colleges can make better predictions of academic success than by relying on a one-at-a-time review of each candidate. Banks use models to grant loans. In bygone times, bankers relied on the three Cs: credit, capacity and character. They asked: Does the applicant have a strong credit record? Does his monthly income leave enough money, after other expenses, to make the payments? Does she seem trustworthy? Those aren t bad rules of thumb, but bankers, like everyone else, are prone to error. Models do a better job of predicting whether a loan will be repaid, and by updating them continually with the latest information, we can make them even more accurate over time. In recent years the use of decision models has surged. The combination of vast amounts of data --- stored in places like the NSA s Utah Data Center [a facility featured early in Rosenzweig s book] --- and increasingly sophisticated algorithms has led to advances in many elds. Some applications are deadly serious. Palantir, based in Palo Alto, Calif., analyzes masses of nancial transactions on an ongoing basis to detect money laundering and This excerpt from "Left Brain, Right Stuff" explains the value and limitations of decision models BY PHIL ROSENZWEIG on to available. ve tion and ther ms. ous and nt w t d c d N fb staP att In recent years the use of decision models has surged. The combination of vast amounts of data --- stored in places like the NSA s Utah Data Center --- and increasingly sophisticated algorithms has led to advances in many elds. 28 March 15, 2014 FCW.COM
March 30, 2014