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NYU - NATSCI - 306
Brain Dysfunctions Addiction Alzheimers disease A.D.H.D attention deficithyperactivity disorder Autism Bipolar disorder Cerebral Palsy Dementia Dyslexia Eating disorders Epilepsy Huntingtons disease Korsakoffs psychosisLou Gehrigs diseasela
NYU - NATSCI - 306
Brain Dysfunctions Addiction Alzheimers disease A.D.H.D attention deficithyperactivity disorder Autism Bipolar disorder Cerebral Palsy Dementia Dyslexia Eating disorders Epilepsy Huntingtons disease Korsakoffs psychosisLou Gehrigs diseasela
NYU - NATSCI - 306
Brain and BehaviorMidterm Study GuideSpring 2011The format of the exam will consist of 9 True/False, 26 Multiple Choice, 2 or 3 fill-in-the-blanks and a 3short answer questions out of a choice of 8. Note: All short answer questions will require you to
NYU - NATSCI - 306
Final (25%) - will cover material that was NOT in the midtermTrue/False (15) 15 pointsMultiple Choice (25) 50 pointsMatching (5) 5 pointsShort Answer (8, but choose 3 to answer) 30 pointsMidterm (25%)Labs (35%) there are 10 labsClass Reports (15%)
NYU - STATS - 18
StatisticsV31.0018.006Chapter 1Describing Data: GraphicalCh. 1-11.1Dealing with UncertaintyEveryday decisions are based on incompleteinformationConsider:nnnWill the job market be strong when I graduate?Will the price of Yahoo stock be higher
NYU - STATS - 18
Chapter 2Describing Data: NumericalCh. 2-1Describing Data NumericallyDescribing Data NumericallyCentral TendencyVariationArithmetic MeanRangeMedianInterquartile RangeModeVarianceStandard DeviationCoefficient of VariationCh. 2-22.1Measures
NYU - STATS - 18
Chapter 3ProbabilityCh. 3-13.1nnnnImportant TermsRandom Experiment a process leading to anuncertain outcomeBasic Outcome a possible outcome of arandom experimentSample Space the collection of all possibleoutcomes of a random experimentEvent
NYU - STATS - 18
Chapter 4Discrete Random Variables andProbability DistributionsCh. 4-1Introduction toProbability Distributions4.1nRandom Variablen Represents a possible numerical value froma random experimentRandomVariablesCh. 4DiscreteRandom VariableCont
NYU - STATS - 18
Chapter 5Continuous Random Variables andProbability DistributionsCh. 5-15.1Continuous Probability DistributionsnA continuous random variable is a variable thatcan take on any value in an intervalnnnnnheight of a personweight of a parceltim
NYU - STATS - 18
Chapter 6Sampling andSampling DistributionsCh. 6-1Tools of Business Statistics6.1nDescriptive statisticsnnCollecting, presenting, and describing dataInferential statisticsnDrawing conclusions and/or making decisionsconcerning a population ba
NYU - STATS - 18
Chapter 7Estimation: Single PopulationCh. 7-1Definitions7.1nAn estimator of a population parameter isnnna random variable that depends on sampleinformation . . .whose value provides an approximation to thisunknown parameterA specific value o
NYU - STATS - 18
Chapter 9Hypothesis TestiningCh. 9-1What is a Hypothesis?9.1nA hypothesis is a claim(assumption) about apopulation parameter:nnpopulation meanExample: The mean monthly cell phone bill of this city is = $42population proportionExample: The p
NYU - STATS - 18
Chapter 11Simple RegressionCh. 11-1Purpose of Regression AnalysisnThe purpose of regression analysis is to:nnPredict the value of a dependent variable based onthe value of at least one independent variableExplain the impact of changes in an inde
NYU - STATS - 18
Chapter 12Multiple RegressionCh. 12-112.1The Multiple Regression ModelIdea: Examine the linear relationship betweenone dependent (Y) & 2 or more independent variables (Xi)Multiple Regression Model with k Independent Variables:Y-interceptPopulatio
NYU - STATS - 18
Chapter 13Additional Topics inRegression AnalysisCh. 13-1Dummy Variable Models(More than 2 Levels)nnConsider a categorical variable with K levelsThe number of dummy variables needed is oneless than the number of levels, K 1nExample:y = house
NYU - STATS - 18
Point Estimation. Methods for Constructing PointEstimators1Random Samples and Distribution FunctionsDenition 1 A population is a group of objects (e.g., individuals, households,rms, cities, states, countries etc.) whose numerical feature, X; is descr
NYU - STATS - 18
Simple Regression ModelSpecication and AssumptionsSuppose we have a population of objects characterized by two random variables- (y; x): We want to investigate the relationship between y and x. In otherwords, we would like to "explain y in terms of x"
NYU - STATS - 18
Multiple Regression ModelMotivation and InterpretationMotivation. Economists often need to estimate and test hypotheses aboutthe joint eect of several variables on the dependent variable. For instance,economists may be interested in testing the consta
NYU - STATS - 18
Alternative Estimators under HeteroscedasticityGLS EstimatorAs we already seen the OLS is ine cient under heteroscedasticity. Then,vewhat is the e cient estimator? It turns out that the most e cient estimator isthe generalized least squares estimator
NYU - STATS - 18
Extensions of Multivariate Regression ModelDummy VariablesMany regressions may contain qualitative explanatory variables, also calleddummy or categorical variables since they indicate dierent categories (e.g.,ethnical groups, regions in the US, partie
St. Leo - COM - 315
CHAPTER 12INVENTORY CONTROL MODELSSOLUTIONS TO DISCUSSION QUESTIONS12-1. Inventory is an important consideration for managers because as much as 50% of the total assets ofa company can be tied up in inventory. Because of this large investment in inven
St. Leo - COM - 315
CHAPTER 4LINEAR PROGRAMMING SENSITIVITY ANALYSISSOLUTIONS TO DISCUSSION QUESTIONS4-1. In most real world situations that are modeled using LP, conditions are dynamic and changing.Hence, input data such as resource availabilities, prices, and costs use
St. Leo - COM - 315
CHAPTER 5TRANSPORTATION, ASSIGNMENT, AND NETWORKMODELSSOLUTIONS TO DISCUSSION QUESTIONS5-1. The transportation model is an example of decision making under certainty since the costs of eachshipping route, the demand at each destination, and the suppl
St. Leo - COM - 315
CHAPTER 6INTEGER, GOAL, AND NONLINEAR PROGRAMMINGMODELSSOLUTIONS TO DISCUSSION QUESTIONS6-1.(a) LP allows only one goal (for example, profit maximization) whereas GP permits multiple goals.(b) LP always optimizes; GP sometimes only satisfices.(c) I
St. Leo - COM - 315
CHAPTER 7PROJECT MANAGEMENTSOLUTIONS TO DISCUSSION QUESTIONS7-1. PERT and CPM can answer a number of questions about a project or the activities within a project.These techniques can determine the earliest start, earliest finish, latest start, and the
St. Leo - COM - 315
CHAPTER 8DECISION ANALYSISSOLUTIONS TO DISCUSSION QUESTIONS8-1. The purpose of this question is to make students use a personal experience to distinguish betweengood and bad decisions. A good decision is based on logic and all of the available informa
St. Leo - COM - 315
CHAPTER 9QUEUEING MODELSSOLUTIONS TO DISCUSSION QUESTIONS9-1. The queuing problem concerns the question of finding the ideal level of service that an organizationshould provide. The three components of a queuing system are arrivals, waiting line, and
St. Leo - COM - 315
CHAPTER 10SIMULATION MODELINGSOLUTIONS TO DISCUSSION QUESTIONS10-1. Advantages of simulation: (1) relatively straightforward; (2) can solve large, complex problems; (3)allows what if questions; (4) does not interfere with real-world systems; (5) allow
St. Leo - COM - 315
CHAPTER 11FORECASTING MODELSSOLUTIONS TO DISCUSSION QUESTIONS11-1. The steps that are used to develop any forecasting system are:1. Determine the use of the forecast.2. Select the items or quantities that are to be forecasted.3. Determine the time h
St. Leo - COM - 340
Introduction to Computers and the InternetThe renaissance of interest in the web that we call Web 2.0 has reached the mainstream.Tim OReilly1Billions of queries stream across the servers of these Internet servicesthe aggregate thoughtstream of humanki
St. Leo - COM - 340
Give us the tools, and we will finish the job.-Sir Winston ChurchillWeb Browser Basics:Internet Explorer and FirefoxOBJECTIVESIn this chapter you will learn:2We must learn to explore all the options and possibilities that confront us in a complex an
St. Leo - COM - 340
3Dive Into Web 2.0Network effects from user contributions are the key to market dominance in the Web 2.0 era.Tim OReillyLink by link, click by click, search is building possibly the most lasting, ponderous, and significant cultural artifact in the his
St. Leo - COM - 340
4Introduction to XHTMLTo read between the lines was easier than to follow the text.Henry JamesHigh thoughts must have high language.AristophanesOBJECTIVESIn this chapter you will learn:Yea, from the table of my memory Ill wipe away all trivial fon
St. Leo - COM - 340
5Fashions fade, style is eternal.Yves Saint LaurentCascading Style Sheets (CSS)OBJECTIVESIn this chapter you will learn:A style does not go out of style as long as it adapts itself to its period. When there is an incompatibility between the style an
St. Leo - COM - 340
6Comment is free, but facts are sacred.C. P. ScottJavaScript: Introduction to ScriptingOBJECTIVESIn this chapter you will learn: The creditor hath a better memory than the debtor.James HowellWhen faced with a decision, I always ask, What would be
St. Leo - COM - 340
7Let's all move one place on.-Lewis CarrollJavaScript: Control Statements IOBJECTIVESIn this chapter you will learn: The wheel is come full circle.-William ShakespeareHow many apples fell on Newton's head before he took the hint!-Robert FrostBa
St. Leo - COM - 340
8Not everything that can be counted counts, and not every thing that counts can be counted.Albert EinsteinJavaScript: Control Statements IIOBJECTIVESIn this chapter you will learn: Who can control his fate?William ShakespeareThe essentials of cou
St. Leo - COM - 340
9JavaScript: FunctionsForm ever follows function.Louis SullivanE pluribus unum. (One composed of many.)VirgilOBJECTIVESIn this chapter you will learn:O! call back yesterday, bid time return.William ShakespeareTo construct programs modularly from
St. Leo - COM - 340
10JavaScript: ArraysWith sobs and tears he sorted out Those of the largest size . . .Lewis CarrollAttempt the end, and never stand to doubt; Nothings so hard, but search will find it out.Robert HerrickOBJECTIVESIn this chapter you will learn: To
St. Leo - COM - 340
11JavaScript: ObjectsMy object all sublime I shall achieve in time.W. S. GilbertIs it a world to hide virtues in?William ShakespeareOBJECTIVESIn this chapter you will learn: Good as it is to inherit a library, it is better to collect one.Augusti
Acton School of Business - CIVIL - 201
CIVL04C03Lecture 5: Distance MeasurementKeith MillerIn partnership withDistance Measuremento To examine techniques used in measuring distance. Tape. Electromagnetic (EDM).o Distances provide Scale to control Position topographic detail Set out
Acton School of Business - CIVIL - 201
Geometrics in SurveyingLecture 6: Stadia TacheometryThe use of theodolite and staff to determineposition and height.Keith MillerIn partnership withStadia TacheometryooUse of stadia to determine distances and heightdifference.To define a method
Acton School of Business - CIVIL - 201
Geometrics in SurveyingLecture 7: Detail SurveysKeith MillerIn partnership withDetail SurveysObjectiveso Understand the requirements of a detail survey, and henceplanning issues.o Appreciate the application of control survey work coveredto date i
Acton School of Business - CIVIL - 201
Geometrics in SurveyingLecture 8: Total StationsKeith MillerIn partnership withTotal StationsObjectives for todayo The Surveying Project to understand the proceduresadopted in a typical survey based project.o Survey Control Recap how to establish
Acton School of Business - CIVIL - 201
Geomatics in SurveyingGeomatics in SurveyingLecture 9:Setting Out StructuresStKeith MillerIn partnership withSetting OutObjectiveso Awareness of responsibilities of the setting outengineer and standards that exist.o Understand the procedure for
Acton School of Business - CIVIL - 201
Geomatics in SurveyingGeomatics in SurveyingLecture 10:Setting Out CurvesKeith MillerIn partnership withSetting Out CurvesObjectiveso Define horizontal curves, vertical curves andcompound curves with applications.o Determine the geometry of the
Acton School of Business - CIVIL - 201
Faculty of EngineeringModule code:CIVL04C02Title : Surveying (1)Examination of January 2009SECTION A COMPULSORY QUESTIONQ1. A level loop was run from a bench mark through the bounds of a new construction site to levelmarks that will be used as poin
Acton School of Business - CIVIL - 201
CIVL04C02 (Geometrics in Surveying), Semester 1, 2009/10Practical Exam Schedule for students in Architectural Engineering9:00Sunday3rdJanuary109552 IbrahimMohamedSalaheldin109593 MamdouhAbdlELHamid109596 MarwanMamdouhKassab10946710949110951310960
Acton School of Business - CIVIL - 201
School of EngineeringCivil Eng. DepartmentCIVL04C031st Semester 2009 / 2010Practical Exam ScheduleID No.STUDENT NAME13109433Ahmed Adel Badr El Din4109434Ahmed Alaa Al-Din109448Ahmed Hesham Mahmoud109452Ahmed Khalid Bauomi7109454Ahmed M
Acton School of Business - CIVIL - 201
CIVL04C03 Practical 1LEVELLINGAimTo undertake a levelling exercise that will establish heights for specified locations relative toa defined reference point. In addition to detailing height values, students are expected to showthat quality control pro
Acton School of Business - CIVIL - 201
CIVL04C03 Practical 2THEODOLITE AND ANGLESAimThrough the observation of a number of rounds of horizontal and vertical angles someassessment is to be made of the combined accuracy achieved by the instrument and the observer.This exercise deals with ho
Acton School of Business - CIVIL - 201
School of EngineeringGEOMATICS IN SURVEYINGCIVL04C03 Practical 3Lecturer:Assistant:Keith MillerMaha Hussien and Mohamed HegazyDETAIL SURVEYAimProduce a survey plan of a part of the BUE campus as defined in the group area plan toinclude boundarie
Acton School of Business - CIVIL - 201
CIVL04C03 Practical ExaminationStadia Tacheometry and LevellingThis is an examination arrive punctually. A schedule is also posted.30 minutes is allowed for field work, and the remaining 30 minutes is for calculations.This paper is available to studen
Acton School of Business - CIVIL - 201
School of EngineeringGEOMETRICS IN SURVEYINGCIVL 04C03 (10 Modular weight: 2hrs. Lecture, 1 hrs. Tutorial/Practical)Professor:Dr. Keith MillerPre-requisites:NoneText Books:Elementary Surveying: An Introduction to Geomatics,C. D. Ghilani and P. R.
Acton School of Business - CIVIL - 201
PointBUEIBUECEastInstrumentReferenceReferenceBearing3.420769605 195.9957629.483621.803NorthHeightInst. Ht.939.11001.532912.309Point details in here.East and North from witness diagrams,Height from result of first levelling exercise.Be
Acton School of Business - CIVIL - 201
CONSTRUCTION TECHNOLOGYCONSTRUCTION TECHNOLOGYIntroductionDr MaguidDr. Maguid H.M. HassanHassanExt. 1413Email: mhassan@bue.edu.egDr AmrDr. Amr HelmyExt. 1416 Room 206 Building AEmail: amr.helmy@bue.edu.egContentsContentsReviewReview Course
Holy Names - BUS - 295W
Netflixs Business Model and Strategy in Rending Movies and TV EpisodesNetflix, founded in 1997 by Reed Hastings is the worlds largest online movie rental service;with revenues of 1.2 billion by the end of 2007. Netflix has a library of 100,000 movie tit
USC - CSCI - CSCI460
CS 460: Artificial IntelligenceInstructor: Prof. K. Narayanaswamy (Swamy), swamy@cs3-inc.comOffice hours: For Instructor by appointment; before/after classLectures: Tuesdays 6 p.m. to 8:50 p.m. at GFS 1182 lectures of 1 hour 15/20 minutes with a break
USC - CSCI - CSCI460
Last Time: Acting Humanly: The Full Turing Test Alan Turing's 1950 article Computing Machinery and Intelligencediscussed conditions for considering a machine to be intelligent Can machines think? Can machines behave intelligently? The Turing test (The
USC - CSCI - CSCI460
Last time: Summary Definition of AI? Turing Test? Intelligent Agents: Anything that can be viewed as perceiving its environment throughsensors and acting upon that environment through its effectors tomaximize progress towards its goals. PAGE (Perce
USC - CSCI - CSCI460
Complexity Why worry about complexity of algorithms?because a problem may be solvable in principle but maytake too long to solve in practiceCS 460, Lecture 41Complexity: Tower of HanoiCS 460, Lecture 42Complexity:Tower of HanoiCS 460, Lecture 4