The SCASA’s 35th Annual Applied Statistics Workshop
Date: Saturday, March 12, 2016
Time: 8:30am to 3:30pm
Place: Arnold and Mabel Beckman Center, Argyros Auditorium, City of Hope, 1500 E. Duarte Road, Duarte, CA 91010 (map is here)
Speaker: Dr. Tim Hesterberg, Senior Ads Quality Statistician at Google
Topic: Bootstrap Methods and Permutation Tests with Practical Applications
Schedule:
8:30am – 9:00am Check-in, Late Registration, Breakfast
9:00am – 10:30am Welcome and Session 1
10:30am – 11:00am Break
11:00am – 12:30pm Session 2
12:30pm – 1:30pm Lunch
1:30pm – 3:00pm Session 3
3:00pm – 3:30pm Raffle (must be present to win)
Registration fees:
Until March 2, 2016 – General $60, Student $10
After March 2, 2016 – General $70, Student $15
Please consider sponsoring your students.
To register and pay, please go to https://www.123signup.com/event?id=ppzpm
Parking information: Parking at City of Hope is free. Either Lot A or G is OK. A is more walking, G is more driving.
Other useful information: Absolutely no food (only water) is allowed inside the auditorium. Breakfast and lunch will be set up in the lobby. Five vegetarian lunches will be ordered. It has always been enough, so if you are vegetarian, you don’t need to worry about lunch.
No vendors or poster contest will be held this year. Vendors would have to get clearance through the department of grant and contracts at COH, which is a hassle.
Abstract:
We begin with a graphical approach to bootstrapping and permutation testing, illuminating basic statistical concepts of standard errors, confidence intervals, p-values and significance tests. We consider a variety of statistics (mean, trimmed mean, regression, etc.), and a number of sampling situations (one-sample, two-sample, stratified, finite-population), stressing the common techniques that apply in these situations. We'll look at applications from a variety of fields, including telecommunications, finance, and biopharm. These methods let us do confidence intervals and hypothesis tests when formulas are not available. This lets us do better statistics, e.g., use robust methods (we can use a median or trimmed mean instead of a mean, for example). They can help clients understand statistical variability. And some of the methods are more accurate than standard methods.
About the speaker:
Dr. Tim Hesterberg is a Senior Statistician at Google. He previously worked at Insightful (S-PLUS), Franklin & Marshall College, and Pacific Gas & Electric Co. He received his Ph.D. in Statistics from Stanford University, under Brad Efron. Hesterberg is author of the "Resample" package for R and primary author of the "S+Resample" package for bootstrapping, permutation tests, jackknife, and other resampling procedures, is co-author of Chihara and Hesterberg "Mathematical Statistics with Resampling and R" (2011), and is lead author of "Bootstrap Methods and Permutation Tests" (2010), W. H. Freeman, ISBN 0-7167-5726-5, and technical articles on resampling. See http://www.timhesterberg.net/bootstrap. Hesterberg is on the executive boards of the National Institute of Statistical Sciences and the Interface Foundation of North America (Interface between Computing Science and Statistics).