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2010 ISIT Plenary LecturenCompletely Random Measures for Bayesian NonparametricsnProfessor Michael I. JordannUniversity of California, BerkeleynnAbstract: Computer Science has historically been strong on data structures and weak on inference from data, whereas Statistics has historically been weak on data structures and strong on inference from data. One way to draw on the strengths of both disciplines is to pursue the study of inferential methods for data structures; i.e., methods that update p
⏲ 38 min 67 sec ✓ 02-Sep-2015
The Organic Chemistry Tutor
⏲ 56 minutes 46 seconds 👁 403.1K
TAF IAS ACADEMY
⏲ 1 hour 2 minutes 3 seconds 👁 103.2K
SPEAKER: Abraham D. Flaxman, Institute for Health Metrics and Evaluation, Dept of Global Health, UWn nTITLE: Simulation and Optimization for Health Resourcesn nABSTRACT:n
⏲ 29 min 27 sec ✓ 11-Jun-2011
The Organic Chemistry Tutor
⏲ 10 minutes 2 seconds 👁 1.1M
LISA (Laboratory for Interdisciplinary Statistical Analysis) is providing a series of evening short courses to help graduate students use statistics in their research. The focus of these two-hour courses is on teaching practical statistical techniques for analyzing or collecting data.nnTuesday, November 10, 2015, 4:30-6:30 pm;nLocation: 1080 Torgersen Hall;nInstructor: Ting Guan;nTitle: Comparing Means and Other Measures of Location between Two Populations by Significance Tests and Effect Size ;
⏲ 35 min 57 sec ✓ 18-Dec-2015
It’s About the Numbers… By Understanding Real Estate Statistics, The Opportunity Tree will Bend to your Will! #KeySuccessIdeas - Opportunity conjures the beauty of the possible and smirks at the “impossible.” Entrepreneurs must become very friendly with the concept of Opportunity and mold it into their Daily Business Reality.nnOpportunity Thinking… Opportunity is not wishful thinking; Opportunity is the Practical Implementation of Daily Checklists and activities that bend results to
⏲ 8 min 22 sec ✓ 20-Aug-2019
LISA (Laboratory for Interdisciplinary Statistical Analysis) is providing a series of evening short courses to help graduate students use statistics in their research. The focus of these two-hour courses is on teaching practical statistical techniques for analyzing or collecting data.nnTuesday, March 15, 4:00-6:00 pm;nLocation: 1100 Torgersen Hall;nInstructor: Ting Guan;nTitle: Comparing Means and Other Measures of Location between Two Populations by Significance Tests and Effect Size;nnMotivati
⏲ 59 min 80 sec ✓ 18-Mar-2016
In today's episode we fly through a real minefield! When landing on a wired heli pad it blows up! How does this explosive competition work and what's the statistical survival chance? Detailed explanations are in our facebook gallery (link below).nnMine field is a 4x6 grid of landing pads (4 columns, 6 rows). In each of the 6 rows is one mine (i.e. 6 mines in total). Heli stands on start pad, pilot throws a die. Die can show 1, 2 or 3 dots. Pilot may then advance to row 1, 2 or 3, respectively, a
⏲ 2 min 72 sec ✓ 16-Dec-2014
LISA (Laboratory for Interdisciplinary Statistical Analysis) is providing a series of evening short courses to help graduate students use statistics in their research. The focus of these two-hour courses is on teaching practical statistical techniques for analyzing or collecting data.nnTuesday, March 15, 4:00-6:00 pm;nLocation: 1100 Torgersen Hall;nInstructor: Ting Guan;nTitle: Comparing Means and Other Measures of Location between Two Populations by Significance Tests and Effect Size;nnMotivati
⏲ 2 min 43 sec ✓ 22-Mar-2016
For More Info: Please visit, zarantech.com/data-science-master-program/nContact: +1 (515) 309-7846 (or) Email - info@zarantech.comn==========================================nCourse Duration:100 hours Live Training + Assignments + Actual Project Based Case Studiesn===========================================nMODULES COVERED IN THIS TRAINING:nnUnit 1: Programming in python and r:nnBelow topics are covered in this Python essentials module for Data Science.nPython & R basics.nConditional and loop
⏲ 20 min 85 sec ✓ 03-Nov-2019
Most of us are happy visualising three-dimensional objects. We can draw them, or make models of them, and so on. Professor Imre Leader, Department of Pure Mathematics and Statistics, asks how would we visualise a four-dimensional object? What would a 'four-dimensional object' even mean? And what about going beyond four dimensions? Co-editor of Combinatorics and Probability co-editor Prof. Imre Leader answers these questions in more in this 2020 Cambridge Science Festival presentation. For more i
⏲ 33 min 39 sec ✓ 31-Mar-2020
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