'Normal dist' diaporamas de présentation

Dr. N. Birkett, Department of Epidemiology & Community Medicine, University of Ottawa

EPI 5344: Survival Analysis in Epidemiology Parametric Methods: exponential and related March 11, 2014. Dr. N. Birkett, Department of Epidemiology & Community Medicine, University of Ottawa. Objectives. Introduce the Accelerated Failure Time model The simple exponential model and MLE

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Normal Distribution Starters

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Statistics & Flood Frequency Chapter 3

Statistics & Flood Frequency Chapter 3. CIVE 6361. Predicting FLOODS. Flood Frequency Analysis. Statistical Methods to evaluate probability exceeding a particular outcome - P (X >20,000 cfs) = 10% Used to determine return periods of rainfall or flows

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Statistics & Flood Frequency Chapter 3

Statistics & Flood Frequency Chapter 3. Dr. Philip B. Bedient Rice University 2006. Predicting FLOODS. Flood Frequency Analysis. Statistical Methods to evaluate probability exceeding a particular outcome - P (X >20,000 cfs) = 10% Used to determine return periods of rainfall or flows

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Bruce Mayer, PE Licensed Electrical & Mechanical Engineer BMayer@ChabotCollege

Engr/Math/Physics 25. Chp7 Statistics-2. Bruce Mayer, PE Licensed Electrical & Mechanical Engineer BMayer@ChabotCollege.edu. Learning Goals. Create HISTOGRAM Plots Use MATLAB to solve Problems in Statistics Probability Use Monte Carlo (random) Methods to Simulate Random processes

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Fast and Extensible Building Modeling from Airborne LiDAR Data

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Overview of Risk and Return

Overview of Risk and Return. What is Risk?. A risky situation is one which has some probability of loss The higher the probability of loss, the greater the risk The riskiness of an investment can be judged by describing the probability distribution of its possible returns.

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Materials for Lecture 20

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Statistical Experimental Design

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Estimation of Allele Frequencies from Quantitative Trait Data

3 rd Place Winning Project , 2009 USPROC. Estimation of Allele Frequencies from Quantitative Trait Data. Author: Kinjal Basu Sujayam Saha Sponsor Professor: S. Ghosh K. Ghosh Indian Statistical Institute, Kolkata, India. Introduction.

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Linear Discriminant Functions

Linear Discriminant Functions. Chapter 3, pp. 77 - . Linear Discriminant Functions. Chapter 1 introduced the concept of a discriminant function y( x ) The vector x is assigned to class C 1 if y( x )>0 and C 2 if y( x )<0.

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