Statistics Colloquium/Seminar Series 2016-2017   [2006-2008] [2008-2009] [2009-2010] [2010-2011] [2011-2012] [2012-2013] [2013-2014] [2014-2015] [2015-2016] [Current Year]   For more information, contact the Colloquium/Seminar Coordinator, (To see Math Dept Colloquia/Seminars, click next: Math Dept Seminar) Fall 2016 Google Talk   Friday, September 9, 2016 CBC-C110, 11:30 am-12:30 pm (refreshments at 11:15 am) Senior Statistician Seattle, Washington Title: Bootstrapping for Learning Statistics [Abstract]  Statistical concepts such as sampling distributions, standard errors, and P-values are difficult for many students. It is hard to get hands-on experience with these abstract concepts.  I think a good way to get that experience is using bootstrapping and permutation tests. I'll demonstrate using a variety of examples. They're not just for students. I didn't realize just how inaccurate the classical methods are until I started checking them using these methods. Remember that old rule of n ≥ 30? Try n ≥ 5000 instead. The methods are also useful in their own right. We use them all the time at Google -- they are easier to use than standard methods (less chance of screwing up), besides being more accurate.   Google Talk   Friday, September 9, 2016 CBC-A110, 2:30 pm-4:40 pm (Jobs Chat Q&A 3:30 pm-4:00 pm) Senior Statistician Seattle, Washington Title: Statistics and Big Data at Google [Abstract]  Google lives on data. Search, Ads, YouTube, Maps, ... - they all live on data. I'll tell some stories about how Google uses data, how Google is always experimenting to make improvements (yes, this includes your searches), and how we adapt statistical ideas to do things that have never been done before.   à This is a fun talk, not technical, suitable for undergrads on up, no statistics background needed. à   Friday, September 30, 2016 CBC-C110, 11:30 am (refreshments at 11:15 am) Department of Mathematics & Statistics University of Southern Alabama Title: Population Selection based on Count Data [Abstract]  The count data are popularly described using binomial, Poisson and negative binomial distributions in managerial applications to study consumer behavior, in entomological and ecological applications to study species' behavior, and in quality control applications to study systems' behavior. For each of these distributions, several solutions under different configurations are available for the problem of selecting a best population among the k available populations. Fixed-sample-size procedures with the indifference zone approach will be discussed. Interesting differences and similarities exhibited by these three distributions in the existence of selection procedures and the consistency of selection procedures will be explored. Spring 2017