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Berkeley - CS - 294
cs294: Statistical Natural Language ProcessingAssignment 5: Treebank ParsingDue: April 16th In this assignment, you will build an English treebank parser. You will consider both the problem of learning a grammar from a treebank and the problem of
Berkeley - CS - 294
cs294: Statistical Natural Language ProcessingAssignment 3: Part-of-Speech TaggingDue: March 7th In this assignment, you will build the important components of a part-of-speech tagger, including a local scoring model and a decoder. Setup: The data
Berkeley - UGBA - 100
Pronunciation Guideugba-100, David RobinsonRightly or wrongly, English has become the de facto language of business. Throughout the world, college students work hard to become fluent in English. However, there are many different varieties of spo
Berkeley - IB - 200
Integrative Biology 200A PRINCIPLES OF PHYLOGENETICSUniversity of California, Berkeley Spring 2008Lab 11: MrBayes LabIntroduction MrBayes uses a Markov Chain Monte Carlo (MCMC) approach to search for trees. There are two phases in an MCMC. The f
Berkeley - IB - 200
Integrative Biology 200A "PRINCIPLES OF PHYLOGENETICS"University of California, Berkeley Spring 2006Distance MethodsDue at the end of class: - Distance matrices and trees for two different distance measures - Tree from one extra distance-based t
Berkeley - BIO - 1
3.0Copyright 2008 by Department of Integrative Biology, University of California-BerkeleyIntroduction to Cladistic AnalysistunicatelampreyCladoselache troutlungfishfrogfour true enamel limbsswimbladder or lung jaws vertebrae skul
Berkeley - BIO - 1
Safety Guidelines for Field ResearchOffice of Environment, Health & Safety University of California, BerkeleyEmergency Phone ListFill in the information for the area where you will be working.Ambulance: _Sheriff: __Police: _Hospital: _
Berkeley - IB - 146
Name _ IB 146 Behavioral Ecology FIRST MIDTERM EXAM (6 pages, 100 points) General instructions: Answer each question as directed. Please make answers clear and concise. Full sentences are not required, but make sure that your answers are complete en
Berkeley - IB - 160
spring bookseach synaesthetics list of associations is idiosyncratic, with no discernible commonalities even among identical twins. But any one persons associations remain very stable over time. This is the basis of the now-standard test for genuine
Berkeley - IB - 200
Integrative Biology 200A Principals of PhylogeneticsUniversity of California, Berkeley Spring 2008Molecular Clocks and Tree DatingToday we are going to use several different methods of testing the molecular clock and estimating node times. We wi
Berkeley - IB - 200
IB 200A "Principles of Phylogenetics"Spring 2008Concatenating Data Sets and Running AnalysesConcatenating Molecular Data Sets Mesquite can concatenate molecular data sets. It is also possible to concatenate molecular and morphological data matri
Berkeley - IB - 133
IB 133: Teaching GuidelinesChecklist for Developing Your Presentation: Design hands-on activities (No lectures!). Your GSI can help. Plan minds-on discussions. Remember your audience. Kids are curious and enjoy learning about themselves. Encour
Berkeley - IB - 153
IB 153L GENERAL PRINCIPLES OF SAMPLING 1) What is a sample? A subset of a population is called a sample of that population. 2) Why sample? a) Limitations of time and money make it unrealistic to observe all elements of many populations. b) If measure
UCF - FIN - 4514
Keeping Costs DownErin E Arvedlund Barron's; Apr 3, 2006; 86, 14; ABI/INFORM Global pg. 39Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.Reproduced with permission of the copyright owner. Fu
UCF - ECO - 7426
1BUEC2570 INTRODUCTION TO ECONOMETRICS LIMDEP DOCUMENT TABLE OF CONTENTS (1) A Step-by-Step Guide to Accessing and Using LIMDEP: Pages 2-14. (2) Short Explanation, With Examples of the Key LIMDEP COMMANDS for BUEC2570: Pages 15-18 (3) Basic LIMDEP
Berkeley - BOOK - 3
Rice-15149bookMarch 10, 200616:21144Chapter 4Expected ValuesMinimizing this with respect to gives the optimal portfolio opt =2 2 2 2 1 + 2For example, if the investments are equally risky, 1 = 2 = , then = 1/2, so the best strate
Berkeley - STAT - 2
Practice midterm Stat 2, summer 2008 60 minutes There are TWENTY questions, which tend to get harder as you go along. A researcher believes cupcakes make people fall asleep. At noon, he feeds cupcakes to a random sample of cupcake-eaters until they a
Berkeley - STAT - 153
STAT 153 Assignment 2 solutions1. (a) MSE(A) = E(x2 2Axt + A2 x2 ) t+l t+l t = Ex2 2AExt + A2 Ex2 t+1 t+l t = (0) 2A(l) + A2 (0)MSE(A) is minimised when 2l MSE(A) = A2 2(l) + 2A(0) = 0 E A = 0(l) (0) = (l)(b) Substituting A = (l)/(0) gives
Berkeley - SOC - 271
From: To: Topic:Trond Petersen Course Participants Descriptives, means, frequencies etc., for dataHere comes the means, standard deviations, minima, maximums, obtained from full sample, N=3958 Descriptive Statistics Variable Mean Std. Dev. Skew.
Berkeley - SOC - 271
To: From: Re: Topic: Handout #:Course Participants Trond Petersen Categorical Dependent Variables Preliminary Issues Lecture Notes #0Agenda 0. 0.1 0.2 0.3 0.4 0.5 0.6 Preliminaries Introductory Remarks Types of Statistical Models Probability Theo
Berkeley - SOC - 271
To: From: Re: Topic: Handout #:Course Participants Trond Petersen Categorical Dependent Variables Logit and Probit Models for Sequential Choices Class Handout #6Agenda 6 6.1 6.2 6.3 6.5 6.5 6.6 Logit and Probit Models for Sequential Choices Intro
Berkeley - SOC - 271
To: From: Course: RE: Topic:Course Participants Trond Petersen Event History Analysis ML Estimation A Simple ExampleML Estimation of Binary ProbabilityConsider the data of n=5 observations: Observation Variable i D_i _ 1 0 2 0 3 0 4 1 5 1 _St
Berkeley - SOC - 271
From: To: RE:Trond Petersen Course participants How to read a table for the chi-square distributionOn Reading the Table Table C (Agresti and Finlay 2001, p. 670) gives critical values for the chisquare distribution. It does so only for the right-
Berkeley - SOC - 271
To: From: Course: RE: Topic:Course Participants Trond Petersen Categorical Dependent Variables Odds and odds-ratios How to do itThere are three steps: Step 1: Step 2: Step 3: The probabilities (proportions) The Odds (ratio of two probabilities) T
Berkeley - CONF - 5
08:00 - 09:00 09:00 - 09:05 09:05 - 09:10Name cards available for those who have registered. Welcome by Elwin Marg on behalf of the Minerva Foundation and the University of California, Berkeley. Introduction by Semir Zeki on behalf of the Institute
Berkeley - CS - 252
CS252 Graduate Computer ArchitectureMotivation: Who Cares About I/O? CPU Performance: 60% per year I/O system performance limited by mechanical delays (disk I/O) Amdahl's Law: system speed-up limited by the slowest part!< 10% per year (IO per s
Berkeley - E - 218
Do Consumers Know Their Willingness to Pay? Evidence from eBay AuctionsHanh Ahlee Stanford University yolee@stanford.edu Ulrike Malmendier Stanford University ulrikem@stanford.eduOctober 2, 2005 VERY PRELIMINARYAbstract According to standard eco
Berkeley - E - 251
Do Disappointing Pay Raises Lower Productivity? Final-Offer Arbitration and the Performance of New Jersey Police Officers*Abstract This paper studies whether on-the-job performance of labor market participants responds to changes in relative compen
Berkeley - E - 234
Econ 234C Corporate Finance Lecture 12: Corporate GovernanceUlrike Malmendier UC BerkeleyMay 1, 2007Outline1. Organization 2. Homework 3 3. Corporate Governance and Executive Compensation Monitoring of Managers (Townsend 1979) Other Topics
UCF - MAR - 3023
Slide 1Back to SchoolAlready?Slide 2Welcome to MAR 3023H4 credit hour course!Slide 3IntroductionsISlide 4Raj Echambadi Ph.D. Marketing Area of specialization: Strategy; especially technology management andloyalty issues Marketi
UCF - MAR - 3023
Slide 1Chapter 2Strategic Planning for Competitive AdvantageSlide 2LOIWhat is Strategic Planning?The managerial process of creating and maintaining a fit between the organizations objectives and resources and evolving market opportunities t
UCF - MAR - 3023
Chapter 15 Advertising and Public RelationsThe Nature and Types of Advertising Defined paid non-personal mass-media Functions of Advertising Social Business EconomicTHE VALUE OF ADVERTISINGincreases the number of units sold and allows l
UCF - MAR - 3023
MAR 3023: Principles of Marketing Fall 2005 Wednesdays, 6:00 8:45 p.m. Classroom: CSB 101Professor: Office: Office Hours: Telephone: Fax: E-Mail: Class Web Page: WebCT Graduate Asst: Office: Office Hours (In person and Online) Graduate Asst Telepho
UCF - MAR - 3023
Slide 1Chapter 12 Marketing Channels and Supply Chain ManagementSlide 2Distribution Channel (PLACE)ManufacturerRetailerBusiness Structure / NetworkDistributorConsumersSlide 3The Nature of Marketing Channels Functions Transactional (p
UCF - MAR - 3023
Josephine Student TA: Wendy Jstude001@student.ucr.edu Assignment # 1 January 30, 2003CONSUMER INFORMATION SEARCH FOR CRANBERRY JUICEInformation Search Usenet Group participants discuss a number of issues related to the taste and nutritional merits
UCF - MAR - 7638
REVISED TENTATIVE SCHEDULE20-Sep-05 Week 5 Theory building and theory testing II. Theory Workshop Why do we need theory? 1. Bagozzi, Richard (1984), A Prospectus on Theory Constructionin Marketing Journal of Marketing, 48 (Winter), 11-29. (CS Requ
UCF - MAR - 7638
Academy of Management Journal 2004, Vol. 47, No. 4, 501522.KNOWLEDGE TRANSFER THROUGH INHERITANCE: SPINOUT GENERATION, DEVELOPMENT, AND SURVIVALRAJSHREE AGARWAL University of Illinois at Urbana Champaign RAJ ECHAMBADI University of Central Florida
UCF - MAR - 3023
Slide 1Chapter 13 RetailingSlide 2IntroductionRetailer An intermediary involved in selling goods and services to ultimate consumers An intermediary that takes title to the goods it handles and redistributes them to retailers, other distributors
UCF - MAR - 3023
Slide 1Chapter 15 Advertising and Public RelationsSlide 2 Defined paid non-personalThe Nature and Types of Advertising mass-media Functions of Advertising Social Business EconomicSlide 3THE VALUE OF ADVERTISINGincreases the number
UCF - MAR - 3023
Slide 1Chapter 8 Decision Support Systems and Marketing ResearchSlide 2Marketing Research Marketing research: The process of planning, collecting, and analyzing data relevant to a marketing decision.Any decision that helps in making informed ma
UCF - MAN - 6286
Slide 1Workshop on Lead User MethodologySlide 2Agree or Disagree? Company A develops an (incrementally) innovative product. The MR department conducts three focus groups of eight existing customers per group and ascertains the feasibility of t
UCF - MAR - 3023
Josephine Student TA: Wendy Jstude001@student.ucr.edu Assignment # 3 January 30, 2003SEGMENTING THE MARKET FOR FROZEN DESSERTS Segmentation variables Several variables differentiate consumers who prefer different kinds of desserts, such as frequenc
UCF - MAR - 3023
Slide 1Chapter 5 CONSUMER Decision MakingSlide 2What is consumer behavior? Activities people undertake when obtaining, consuming and disposing of products and services. B2C and B2B markets.Slide 3What Is Consumer Marketing?The marketing of
UCF - MAR - 3023
MAR 3023 OV 97: Principles of Marketing (4 Credit Hours) Fall 2007 Video streaming section: Main campusProfessor: Office: Office Hours: Telephone: Fax: E-Mail: Class Web Page: WebCT Virtual Office Hours Dr. Raj Echambadi BA2 308R, Department of Mar
UCF - MAR - 3023
MAR 3023 Honors: Marketing Fall 2008 Tuesdays, 6:00-8:45 p.m. Professor: Office: Office Hours: Telephone: Fax: E-Mail: Class Web Page: COURSE OBJECTIVES: To gain a basic understanding of the functions of marketing. To develop a working vocabulary of
UCF - MAR - 6816
MAR 6816 Strategic Marketing Management Section 0068 Fall 2005 BA - 110 Mondays, 10:30 1:15 p.m.Professor: Office: Phone: Fax: Email: Class Website: Office Hours:Dr. Raj Echambadi BA2 308R (407) 823-5381 (407) 823-3891 raj.echambadi@bus.ucf.
UCF - MAN - 6286
Slide 1_ _MAN 6286 Strategic Innovation Management_ _ _ __ _Slide 2Agenda for the Day Introduction. Overview of the course macro-level overview of strategy / innovation management / strategic innovation._ __ _ _ _ _ _ Syllabus and cou
UCF - MAR - 3023
Chapter 3Social Responsibility, Ethics, and the Marketing EnvironmentEnvironmental ScanningEnvironmental Scanning is the process of collecting information about the external marketing environment to identify and interpret potential trends. Inter
UCF - CAP - 5415
Announcements PS 2 is available Please read it by Thursday During Thursday lecture, I will be going over it in some detail Monday - Computer Vision Distinguished Lecturer seriesLecture 7: Edge DetectionCAP 5415: Computer Vision Fall 2007Edge
UCF - EGN - 3420
Su 95 EGN 3420EXAM 2Name _DO ANY 4 PROBLEMSProblem 1 (25 pts)Grade: Y_, N_The following data points are to be approximated by a straight line:xi yi0 01 11 22 33 3A) Find the equation of the Least Squares regression line thru
UCF - EGN - 3420
SP 96 EGN 3420Exam 3Name _DO ANY 3 PROBLEMS Show All Work! Use Only Methods Discussed In Class! Problem 1 (35 pts) /2 Estimate sinx dx 0 A) Using Trapezoidal Integration with 10 equally spaced intervals. B) Using Simpsons 1/3 Rule with 10 equa
UCF - EGN - 3420
ARBITRARY UNKNOWNSThe echelon form of the augmented matrix confirms the existence of arbitrary unknowns, i.e. a consistent system of equations in which one or more variables can be chosen arbitrarily There are several ways to establish if indeed a c
UCF - EEL - 4851
EEL 4851 Engineering Data Structures Summer 2005Office: Office hours: Phone Email: Web: T.A.s Textbook: Prerequisites: Goals: ENGR1-211 Monday and Wednesday 12:30 to 3:30 823-3987 fgonzale@pegasus.cc.ucf.edu http:/pegasus.cc.ucf.edu/~fgonzale/ HW Gr
Berkeley - MATH - 185
Mathematics 185 Fall 2005 Michael Christ Lecture 14 (Tuesday 10/18/2005) Cauchys Theorem (concluded) and some consequences Our rst job today is to nish proving Cauchys theorem. Let be any step contour which satises the nonwinding hypothesis. Last
Berkeley - MATH - 55
Mathematics 55 Spring 2005 Lecture 32 (Friday 4/15/2005) Solving linear constant-coecient recurrence relations Please read 6.3 for Monday. Today we discuss the solution of constant-coecient linear recurrence relations in the homogeneous case an = c1
Berkeley - MATH - 55
Mathematics 55 Spring 2005 M. Christ Midterm Exam #1 Postmortem Comments1 Distribution of scores: Out of 100 points, scores ranged from a high of 96 to a low of 22. The 95th percentile score was 89; 90th percentile was 81; 75th was 76; the median w
Berkeley - MATH - 55
Mathematics 55 Spring 2005 Lecture 38 (Friday 4/29/2005) Graphs (Intro) Announcements. Problem set 12 has been (partially at least) posted. Note that the rst group of problems are from 6.6; there had been a typo in the original announcement (correct
Berkeley - MATH - 55
Mathematics 55 Spring 2005 Lecture 31 (Wednesday 4/13/2005) Recurrence relations Announcements. Please read 6.2 if you have not already done so, and begin reading 6.3. A handout on counting problems/techniques was posted Monday on the course web pa
Berkeley - MATH - 185
Mathematics 185 Fall 2005 Michael Christ Lecture 4 (Thursday 9/8/2005) (Complex) Power Series Announcements. Class meets in 289 Cory Hall for the remainder of the semester. Problem set 2 is now posted on the course web page. Solutions to selecte
Berkeley - MATH - 185
Mathematics 185 Fall 2005 Michael Christ Lecture 13 (Thursday 10/13/2005) Cauchys Theorem (2nd installment) On Tuesday we stated Cauchys theorem, and took a couple of very signicant steps towards proving it, handling the general case of a star-shap