# Register now to access 7 million high quality study materials (What's Course Hero?) Course Hero is the premier provider of high quality online educational resources. With millions of study documents, online tutors, digital flashcards and free courseware, Course Hero is helping students learn more efficiently and effectively. Whether you're interested in exploring new subjects or mastering key topics for your next exam, Course Hero has the tools you need to achieve your goals.

2 Pages

### hw5-sol

Course: CS 540, Fall 2002
School: Wisconsin
Rating:

Word Count: 257

#### Document Preview

for Solution Written Part of Homework 5, CS540, Fall 2008 Question 1 (a) P(Y|X)=(0.70+0.015)/(0.70+0.015+0.10+0.02)=0.856 (b) P(Y|X,Z)=0.70/(0.70+0.10)=0.875 (c) P(Y)=(0.70+0.015+0.08+0.01)/(0.805+0.195)=0.805 (d) P(X,Z)=(0.70+0.10)/(0.70+0.10+0.015+0.02+0.08+0.07+0.01+0.005)=0.80 (e) Since P(X)=0.835, P(Z)=0.95, and P(X)*P(Z)!=P(X,Z), so the data is not consistent with X and Z being independent. Question 2 T:...

Register Now

#### Unformatted Document Excerpt

Coursehero >> Wisconsin >> Wisconsin >> CS 540

Course Hero has millions of student submitted documents similar to the one
below including study guides, practice problems, reference materials, practice exams, textbook help and tutor support.

Course Hero has millions of student submitted documents similar to the one below including study guides, practice problems, reference materials, practice exams, textbook help and tutor support.
for Solution Written Part of Homework 5, CS540, Fall 2008 Question 1 (a) P(Y|X)=(0.70+0.015)/(0.70+0.015+0.10+0.02)=0.856 (b) P(Y|X,Z)=0.70/(0.70+0.10)=0.875 (c) P(Y)=(0.70+0.015+0.08+0.01)/(0.805+0.195)=0.805 (d) P(X,Z)=(0.70+0.10)/(0.70+0.10+0.015+0.02+0.08+0.07+0.01+0.005)=0.80 (e) Since P(X)=0.835, P(Z)=0.95, and P(X)*P(Z)!=P(X,Z), so the data is not consistent with X and Z being independent. Question 2 T: take the homework F: finish the homework Given: P(F)=0.9, P(!T|F)=0.01, P(!T|!F)=0.5 So, P(F|!T)=P(F,!T)/P(!T)=(0.01*0.9)/(0.01*0.9+0.5*0.1)=0.153 Question 3 (a) P(E,B,C)=sigma_A(sigma_D(P(A,B,C,D,E))) = sigma_B(sigma_C(P(A)*P(B|A)*P(C|B)*P(D|A,B)*P(E|D))) =0.8*0.2*0.95*0.85*0.60+0.8*0.2*0.95*0.15*0.50+0.2*0.9*0.95*0.15*0.60+0.2*0.9*0.95*0.85* 0.50=0.177 P(!E,B,C)= sigma_A(sigma_D(P(A,B,C,D,!E))) = sigma_B(sigma_C(P(A)*P(B|A)*P(C|B)*P(D|A,B)*P(!E|D))) =0.8*0.2*0.95*0.85*0.40+0.8*0.2*0.95*0.15*0.50+0.2*0.9*0.95*0.15*0.40+0.2*0.9*0.95*0.85* So, 0.50=0.146 P(E|B,C)=0.177/(0.177+0.146)=0.548 (b) P(D|E,A)=sigma_B(sigma_C(P(A,B,C,D,E))) = sigma_B(sigma_C(P(A)*P(B|A)*P(C|B)*P(D|A,B)*P(E|D))) =0.8*0.2*0.95*0.85*0.60+0.8*0.2*0.05*0.85*0.60+0.8*0.8*0.5*0.25*0.60+0.8*0.8*0.5*0.25*0. 60=0.178 P(!D|E,A)=sigma_B(sigma_C(P(A,B,C,!D,E))) = sigma_B(sigma_C(P(A)*P(B|A)*P(C|B)*P(!D|A,B)*P(E|!D))) =0.8*0.2*0.95*0.15*0.50+0.8*0.2*0.05*0.15*0.50+0.8*0.8*0.5*0.75*0.50+0.8*0.8*0.5*0.75*0. 50=0.2...

Find millions of documents on Course Hero - Study Guides, Lecture Notes, Reference Materials, Practice Exams and more. Course Hero has millions of course specific materials providing students with the best way to expand their education.

Below is a small sample set of documents:

Wisconsin - CS - 540
CS 540Fall 2008CS 540: Introduction to Artificial Intelligence Homework Assignment #3: CSP and Logic Assigned: Friday, October 10 Due: Monday, October 20 Late Policy: Homework must be handed in by noon on the due date and electronically turned in
Wisconsin - CS - 540
CS540: Introduction to Artificial Intelligence Homework assignment #1: Decision TreesAssigned: September 10, 2008 Due: September 24, 2008 Hand in your homework:This homework assignment includes written problems and programming in Java. Hand in hard
Wisconsin - CS - 540
-| || LECTURE 19: Neural Networks || | | November 10, 1994 || ||
Wisconsin - CS - 540
- | | | Lecture 4: Common Lisp (Chap 2) | | | | Feb
Wisconsin - CS - 540
****CS 540****Lecture 4: September 15, 1994**** Prepared by: Ada Sung****More Lisp=Another Example of Iteration in Lisp-(defun iter-reverse(l) (let (result nil) (loop (if (end
Wisconsin - CS - 736
SCALABILITY OF EXT2Yancan Huang, Guoliang Jin May 13, 2008MOTIVATIONGraph for createMOTIVATIONGraph for openMOTIVATIONSame method, different graphs: Code for create:asmlinkage long sys_creat(const char _user * pathname, int mode)
Wisconsin - CS - 736
Pachyderm: The Web Proxy that Never Forgets.Alison Krautkramer sisko1@cs.wisc.edu Jing Li jing@cs.wisc.edu Remzi Arpaci-Dusseau remzi@cs.wisc.eduComputer Sciences Department University of Wisconsin 1210 West Dayton Street Madison, WI 53705 Decembe
Wisconsin - CS - 537
UNIVERSITY of WISCONSIN-MADISON Computer Sciences DepartmentCS 537 Introduction to Operating Systems Andrea C. Arpaci-Dusseau Remzi H. Arpaci-DusseauJournaling File SystemsQuestions answered in this lecture:Why is it hard to maintain on-disk con
Wisconsin - CS - 537
UNIVERSITY of WISCONSIN-MADISON Computer Sciences DepartmentCS 537 Introduction to Operating Systems Andrea C. Arpaci-Dusseau Remzi H. Arpaci-DusseauDynamic Memory AllocationQuestions answered in this lecture:When is a stack appropriate? When is
Wisconsin - CS - 537
* Address Spaces *In the early days, building computer systems was easy. Why, you ask? Becauseusers didn't expect too much. It is those darned users with their expectationsof &quot;ease of use&quot;, &quot;high performance&quot;, &quot;reliability&quot;, and so forth that re
Wisconsin - CS - 537
[SMALLER PAGE TABLES: OR HOW TO STOP FILLING MEMORY WITH THOSE DARN THINGS]We now tackle the second problem that paging introduces: page tables are toobig. We start with out a linear page table. As you might recall (or mightnot, this is getting p
Wisconsin - CS - 537
* Log-structured File Systems *In the early 90's, a group at Berkeley led by Professor John Ousterhout andgraduate student Mendel Rosenblum developed a new file system known as thelog-structured file system [1]. Their motivation to do so was bas
Wisconsin - CS - 537
* The Fast File System *When UNIX was first introduced, the UNIX wizard himself Ken Thompson wrote thefirst file system. We will call that the &quot;old UNIX file system&quot;, and it wasreally simple. Basically, it looked like this on the disk:Super bl
Wisconsin - CS - 537
* Locks *From the last note, we saw that we had a fundamental problem in concurrentprogramming: we would like to execute a series of instructions atomically, butdue to the presence of interrupts, we couldn't. In this note, we thus attackthe pro
Wisconsin - CS - 252
Introduction to Computer EngineeringCS/ECE 252, Fall 2007 Prof. Mark D. Hill Computer Sciences Department University of Wisconsin MadisonChapter 1 Welcome AboardSlides based on set prepared by Gregory T. Byrd, North Carolina State UniversityC
Wisconsin - CS - 252
Introduction to Computer EngineeringCS/ECE 252, Spring 2007 Prof. Mark D. Hill Computer Sciences Department University of Wisconsin MadisonPlace On Desk IPod Laptop Treo Etc. All Computers Software/Hardware separation keyComputers! Engi
Wisconsin - CS - 701
Compiling for the Intel ItaniumTM ArchitectureCompiler TricksSteve Skedzielewski Intel CorporationRAgendaArchitecturePrinciples Compiler Bag of Tricks Speculation Predication Branching Loop GenerationRTraditional Architectures: L
Wisconsin - CS - 701
qpt_stats(1) UNIX Programmer's Manual qpt_stats(1)NAME qpt2_stats - Produce Program Profiles for qpt2SYNTAX qpt2_stats [-c file -f file -i file -Rd -Rh# -Rp# -Rs -v -Wd file -Wfb file] a.outDESCRIPTION qp
Wisconsin - ECE - 539
-1.5880643e-001 7.6568794e-001 2.2590349e-002 9.9988994e-001 -2.2855274e-001 5.7218924e-001 4.7974690e-001 -1.3737110e-001 3.4079018e-002 9.9959462e-001 2.3730599e-001 7.0055420e-001 -1.2958644e-001 8.3175797e-001 -5.5
Wisconsin - ECE - 539
2.1340624e-001 7.5672327e-001 -5.2103639e-001 -6.0533025e-001 -1.3913797e-001 2.0693860e-001 -1.1231593e-001 4.0004556e-001 2.5331727e-001 5.0603659e-001 1.9155456e-001 1.1482365e+000 -5.2876239e-001 -1.2066207e+000 2.2735487e-001 4
Wisconsin - ECE - 539
Matlab Tutorial Supplemental Notes (c) copyright 1997 by Yu Hen Hu0. Prompt: &gt; Comment: % Help: help Separation: , or ; (not display) Quit: quit Interrupt:
Wisconsin - ECE - 539
Integration of Advanced Automotive Engine Simulation Methods Using Neural NetworkYongsheng HeABSTRACTDynamic powertrain models using Simulink include modular models to simulateautomotive engine, transmissions, driveline, and vehicle dynamics.
Wisconsin - ECE - 539
Title: Long Term Pavement Performance (LTPP) Data Analysis forQuantifying contribution of M&amp;C variables on Pavement Performance UsingNeural Network Approach. Choi, Jae-hoOne of the most difficult tasks in any management system is establishingt
Wisconsin - ME - 363
Homework #14 Due December 12, 2007ME 363 - Fluid MechanicsFall Semester 20071] A delivery vehicle carries a long sign on top. The sign is very thin in and out of the page. If the sign is very thin and the vehicle moves at 65 mi/hr, (a) estimate
Wisconsin - ME - 363
Final Exam May 15, 2008ME 363 - Fluid MechanicsSpring Semester 2008Problem 1a (5 points) A 6-mm diameter hole is punched near the bottom of a 32-oz drinking cup full of cold water ( = 1000 kg/m3, = 0.0018 kg/m-s). Estimate the velocity of the s
Wisconsin - ME - 363
Name _ME363 Exam 3/Fall 2006Honor Statement:Signed:_1Name _Concept Questions: Problem 1: Problem 2: Problem 3: Problem 4:/40 _/10 /15 _/19 /16Total:/1002Name _For the Concept Questions, pleasethe correct answer.a. b. c. d.
Wisconsin - ME - 363
&lt;?xml version=&quot;1.0&quot; encoding=&quot;UTF-8&quot;?&gt; &lt;Error&gt;&lt;Code&gt;InternalError&lt;/Code&gt;&lt;Message&gt;We encountered an internal error. Please try again.&lt;/Message&gt;&lt;RequestId&gt;E1780E161C15D7E7&lt;/RequestId&gt;&lt;HostId&gt;G+Zuc2bMt/UxaH3+DVX3 QoAIw2vvEkl2QQktkcypnV/2OhVeenRNPa6A8rwt
Wisconsin - ME - 363
ees code:TA = 20 [C] PA = 101325 [Pa] PL = PA rho = DENSITY(Water,T=TA,P=PA) mu = VISCOSITY(Water,T=TA,P=PA) zA = 174 [m] zB = 152 [m] zC = zB zD = zC zE = zD zF = zE zG = 91 [m] zH = zG zI = zH zJ = zI zK = zJ zL = 104 [m] L = 760 [m] L_CD = 152 [m
Wisconsin - ME - 361
Homework #3 traditional part Due Wednesday September 17, 2008ME 361 - ThermodynamicsFall Semester 20081] {work this problem in EES} Ethanol can be consumed by humans as well as used as a fuel in engines. As a beverage, ethanol has 200 calories
Wisconsin - ME - 361
5-58 Helium is compressed by a compressor. For a mass flow rate of 90 kg/min, the power input required is to be determined. Assumptions 1 This is a steady-flow process since there is no change with time. 2 Kinetic and potential energy changes are neg
Wisconsin - ME - 361
exam 1 could look roughly like this: exam 1 could look roughly like this: &quot;exam 1 practice set 2&quot; 3-51 4-29 solutions 3-51 A rigid tank that is filled with saturated liquid-vapor mixture is heated. The temperature at which the liquid in the tank is c
Wisconsin - ME - 361
9-23 A Carnot cycle with the specified temperature limits is considered. The net work output per cycle is to be determined. Assumptions Air is an ideal gas with constant specific heats. Properties The properties of air at room temperature are cp = 1.
Wisconsin - ME - 361
Exam 3 problems &amp; data this sheet NOT GRADED Nov 25, 2008ME 361 - ThermodynamicsFall Semester 20081] {60 points} Consider the ideal cycle shown on the P-v diagram below. This cycle is to be executed on air in a closed system in a free-piston/c
Wisconsin - ME - 361
Homework #11 Due Wednesday, October 29, 2008ME 361 - ThermodynamicsFall Semester 20081] A steady process generates entropy at a rate of 1 W/K. A thermodynamics student, having learned that entropy generation is in general a bad thing, wonders ho
Wisconsin - ME - 363
Class # 3ME363 Spring 200805/01/091Outline Newtonian and non-Newtonian fluids Surface tension Superhydrophobic surfaces Classification of fluids motions05/01/092couette flowViscositydu ~ dy du = dyviscosity - Newtonian apparen
Wisconsin - ME - 363
Class # 15ME363 Spring 200805/01/091Outline Bernoulli equation Momentum equation with accelerating control volumes05/01/092Momentum EquationBasic Law, and Transport Theorem05/01/093Momentum Equation for Inertial Control Volume
Wisconsin - ME - 363
Class # 19ME363 Spring 200805/01/091OutlineFirst law of thermodynamics05/01/092Reynolds Transport TheoremChange of N Flux in Flux outV e=u + + gz 22First law of thermodynamicsBasic Law, and Transport TheoremV e=u + + gz 2
Wisconsin - ME - 363
Class # 37ME363 Spring 200805/01/091OutlineBoundary layer05/01/092Boundary layerBoundary layerBoundary layerBoundary layerBoundary layerBoundary layerBoundary layerBoundary layerBoundary layerBoundary layerBoundar
Wisconsin - ME - 363
Class # 11ME363 Spring 200805/01/091Outline Conservation of momentum Example problems05/01/092Momentum EquationMomentum Equation for Inertial Control Volume05/01/093Reynolds Transport TheoremChange of NFlux inFlux out
Wisconsin - ME - 363
Class # 18ME363 Spring 200805/01/091Outline HW 6 Angular momentum equationEuler's turbine formula05/01/092Reynolds Transport TheoremChange of N Flux in Flux outAngular Momentum EquationBasic Law, and Transport TheoremAngul
Wisconsin - ME - 363
Problem Air is flowing through a square duct made of commercial steel at a specified rate. The pressure drop and head loss per ft of duct are to be determined. Assumptions 1 The flow is steady and incompressible. 2 The entrance effects are negligible
Wisconsin - ME - 363
&lt;?xml version=&quot;1.0&quot; encoding=&quot;UTF-8&quot;?&gt; &lt;Error&gt;&lt;Code&gt;InternalError&lt;/Code&gt;&lt;Message&gt;We encountered an internal error. Please try again.&lt;/Message&gt;&lt;RequestId&gt;1E20665F304798A0&lt;/RequestId&gt;&lt;HostId&gt;0pp5xAZLW0ASLPti5wL4 rnacSWc1biyGO5e1CKe+De9Nz48cIbzGjzN+MaQQ
Wisconsin - ME - 601
Section IBooks:Physics of MicrofluidicsP.Tabeling, H.Bruus, N-T.Nguyen, P-G de Gennes1. Physics at micrometer scale, scaling laws, understanding implications of miniaturization (Ch. 1 Tabeling) 2. Hydrodynamics at micrometer and nanometer scale
Wisconsin - ME - 601
Contact info Homepage: http:/homepages.cae.wisc.edu/~tnk/me_601/ Office Hours: 2:20 pm - 3:30 pm, Tu - Th Office: ME 2238 E-mail: tnk@engr.wisc.edu Class: ME 2108
Wisconsin - HOMEPAGES - 552
Mikko Lipasti Fall 2005 ECE/CS 552: Introduction to Computer Architecture ASSIGNMENT #4 Due Date: In class November 16th, 2005 This homework is to be done individually. Total 4 Questions, 80 points 1. (5 points) Cache Configurations Consider a system
Wisconsin - CAE - 552
Mikko Lipasti Fall 2005 ECE/CS 552: Introduction to Computer Architecture ASSIGNMENT #4 Due Date: In class November 16th, 2005 This homework is to be done individually. Total 4 Questions, 80 points 1. (5 points) Cache Configurations Consider a system
Wisconsin - IE - 476
Dealing with Team Problemso Communication Problem Use email Use website Use the telephoneo Time Conflict Establish specific free time for team meeting Make a team scheduleo Commitment Issues Encourage active involvement Delegate work load
Wisconsin - ECE - 353
ECE 353 Introduction to Microprocessor SystemsReview/Assessment Slides for Quiz #3 ADuC7026 Memory System Timing AnalysisImplement a 32k x 16 memory bank, using only the memory devices shown below. Select the proper number of memory device
Wisconsin - ENGR - 565
Keyboarding Hands, Wrists, ElbowsIE 565 Lecture 4 February 9th, 2005Working of the Arms and Hands The motion of the upper arm is controlled by shoulder muscles. The muscles of the upper arm control the forearm. Simply holding the arms, withou
Wisconsin - ENGR - 565
Lighting and VisionIE 565 Lecture 6 February 23rd, 2005The Visual System5 421 31=cornea and lens 2=light received on the retina 3=transmission of optic signals along the optic nerve to the brain 4=neurons controlling the optic mechanisms
Wisconsin - ENGR - 565
Anthropometrics, Office Design, and Work-related Musculoskeletal Disorders (WRMDs)IE 565 Lecture 2 January 26th, 2005What is Anthropometry? Definition: The science that deals with measuring size, weight and proportions of the human body. The r
Wisconsin - ENGR - 691
Measuring and Assuring Nursing Home QualityDavid R. Zimmerman, Ph. D.Center for Health Systems Research and Analysis University of Wisconsin - Madisonwww.chsra.wisc.eduContextq q18,000 Nursing Homes in the U.S. About 430 in WisconsinAppr
Wisconsin - ENGR - 691
Design/Quality/Operations Research Concepts and MethodsPhoto: www.ideo.comIE 691: Intro. to HSESession 4: Design/Quality/OR Concepts and MethodsPage 1/27Observation Common to most ethnographic research Sometimes perception, not objectiv
Wisconsin - ENGR - 691
Internet Marketing Online Seminar SeriesBob Wallach American Marketing AssociationA wealth of information is available for marketing professionals at www.MarketingPower.comThe #1 marketing site on the webCommonly Asked Questions Questions C
Wisconsin - ENGR - 691
Class Outline - IE 691 - March 24Prepared for Professor ZimmermanTitle: Implementing &amp; sustaining change at work and home. Learning Objectives: Gain a better understanding of why change is so difficult and how industrial engineers and managers can
Wisconsin - ENGR - 466
Idea GenerationAgenda for todayProblem Formulation Needs Assessment Engineering design: ConceptualIdea Generation Embodiment Detail Methods for generating ideasSolution SearchFeedback MeasurementChange ManagementIE 466: Lecture 9,
Wisconsin - ENGR - 663
Stress ReductionWorkplace and Job RedesignWhat is a Good Workplace Loyalty,Trust, Fairness Commitment to Employees Welfare Excellence in Business Operations Equitable Rewards (pay, promotion, bonus) Good Benefits (health care, retirement,
Wisconsin - ENGR - 323
Shortest Route ProblemxFind the shortest path from an origin to a destination:Minimizedistance, cost, or travel timexNetwork consists of undirected arcs or links:Eacharc is associated with a &quot;distance&quot; &gt;=0xLike transportation problem
Wisconsin - ENGR - 320
IE 320/321 1. An automated optical scanner looks for defects on a continuous sheet of metal. If the metal is being produced according to specifications (the process is &quot;in control&quot;), then defects should occur at a rate of 1 defect per 50 square meter
Wisconsin - ENGR - 320
Project 01(Due March 13, 2003 11am, Weight: 10% of final grade)Part OneIdentify a random phenomenon in the real world that you plan to model. Most interesting phenomena will probably have both an arrival and a service process at a minimum. Exampl
Wisconsin - ENGR - 320
IE 320/321 September 10, 2002 1. It is known that diskettes produced by a certain company will be defective with probability .01 independently of each other. The company sells the diskettes in packages of 10 and offers a money-back guarantee that at