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### lec9

Course: STAT 4710, Fall 2009
School: Maryville MO
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to Introduction Mathematical Statistics Lecture 9 09-25-2007 1 Announcements 2 About the Quiz Must remain 5 minutes. Schedule is tight. The problems will be posted on web before the lecture.You get more time to work on it. Quiz will be closed book/lecture. Show your work. No work, no credit. Solutions to quiz problems will be given together with the homework solution per week. 3 About the handouts New...

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Maryville MO - STAT - 4640
Statistics 4640/7640: Introduction to Bayesian Data Analysis T, Th 12:30 1:45pm; Laerre E3404Instructor: Oce: Oce Phone: Oce Hours: e-mail: Prerequisite: Dr. Fei Liu 134K Middlebush (573) 882-5771 Tuesday 8:0010:00 am liufei@missouri.edu Students t
Maryville MO - STAT - 4710
Introduction to Mathematical StatisticsLecture 8 09-13-20071Tasks Expectation Gamma distribution Exponential distribution Chi-Squared distribution2Expectation Def. (expectation) For X continuous, theexpected value of H(X) is defined as
Maryville MO - STAT - 4710
Introduction to Mathematical StatisticsLecture 10 09-27-200715 Minute Quiz Problem 4.43 (P146) Let X denote the time Find P(X &lt; 15). The fastest 5% of repairs take at most howmany hours to complete?(1.67) = 0.9525,in hours needed to corre
Maryville MO - STAT - 4710
Course Syllabus for 4710/7710 Introduction to Mathematical Statistics Session 2General InformationInstructor: Fei Liu Class time: 9:30 am - 10:45 am T and Th Location: Middlebush 13 Office: Middlebush 134K Office hour: T 2:00pm - 3:00pm and W 1:00
Maryville MO - STAT - 4710
Introduction to Mathematical StatisticsLecture 16 10-18-20071Quiz 14 Given the following m.g.f. Identify the familyto which the random variable belongs in each case, and give the numerical values of pertinent distribution parameters. Explain w
Maryville MO - STAT - 4710
Introduction to Mathematical StatisticsLecture 14 10-11-20071Quiz 12 The observed values of the statistics50 50xi = 63707 ,i=1 i=1x2 = 154924261 . i Would you be surprise to observe anotherdata equals 1270? Find the sample variance a
Maryville MO - STAT - 4710
Introduction to Mathematical StatisticsLecture 15 10-16-20071Quiz 13 Use the method of moments and maximum Are the estimators unbiased? Why or whynot? likelihood method, respectively, to estimate the parameter p of a geometric distribution.
Maryville MO - STAT - 4710
Introduction to Mathematical StatisticsLecture 12 10-04-20071Quiz 10 The joint density for (X,Y) is given byfXY (x, y) = 1/x 0 &lt; y &lt; x &lt; 1 . Find E(X), E(Y), E(XY).2Tasks Expectation Covariance Correlation Conditional density Curves
Maryville MO - STAT - 4710
Introduction to Mathematical StatisticsLecture 1 08-21-20071Tasks Overview of statistics Introducing probability Sample space and events Mutually exclusive events2Statistics Overview Statistics: explain the observed, try to predict. D
Maryville MO - STAT - 4710
Introduction to Mathematical StatisticsLecture 3 08-28-20071Tasks Axioms &amp; properties of probability Conditional probability independence2Axioms of probability Let S denote the sample space:P (S) = 1for every event A.P (A) 0Let
Maryville MO - STAT - 101
Stat 101: Lecture 4Summer 2006Area under Normal CurvePercentage p is somewhat known, nd the value.1. Divide the region into 4 parts. Find the percentage of the middle two. 2. Find z. 3. Decide the sign of the value.Value is somewhat known, n
Maryville MO - STAT - 101
Stat 101: Lecture 3Summer 2006OutlineAnswer QuestionsAreas Under the Normal CurvesThe Continuity CorrectionStatistical Graphics (on Maps)Weighted AverageMajor A Major B TotalMale 72 / 90 2 / 10 74 / 100Female 4/5 9 / 45 13 / 50T
Maryville MO - STAT - 101
Stat 101: Lecture 7Summer 2006OutlinePermutations and Combinations Binomial Probability Poisson Probability Some Exercises Bayes RulePermutations and CombinationsTo arrange n distinct objects in a line, the number of ways are, n! = n (n 1
Maryville MO - STAT - 101
Stat 101: Lecture 13Summer 2006OutlineAnswer QuestionsThe Current Population SurveyConfidence Intervals for AveragesThe Current Population SurveyThe Bureau of Labor statistics administers the Current Population Survey (CPS), which is pe
Maryville MO - STAT - 101
Stat 101: Lecture 10Summer 2006OutlineAnswer QuestionsRandom SamplesBiasProblemsRandom SamplesIn a simple random sample of n units from a population, each unit is equally likely to be chosen, each pair of units is equally likely to be
Maryville MO - STAT - 101
Stat 101: Lecture 20Summer 2006OutlineSome HistoryHow to BootstrapExampleSome HistoryA lot of theoretical statistics has focused on developing methods for setting condence intervals and testing hypotheses. A key tool for doing this is t
Maryville MO - STAT - 101
Lesson Plan Answer Questions Summary Statistics Histograms The Normal Distribution Using the Standard Normal Table12. Summary StatisticsGiven a collection of data, one needs to find representations of the data that facilitate understanding
Maryville MO - STAT - 101
Stat 101: Lecture 12Summer 2006OutlineAnswer Questions More on the CLT The Finite Population Correction Factor Condence Intervals ProblemsMore on the CLTRecall the Central Limit Theorem for averages: X EV N(0, 1) sd/ n where EV is the m
UVA - CS - 101
CS101XSpring2008Name_EMAILID_ Thispledgedexamisopentextbook,cribsheet,andtwopagesofnotes.Itisclosedcalculatorandneighbor.Youmay onlyuseyourmachinetoaccessthecribsheet,andthedocumentssectionoftheclasswebsite Page1:Classparticipation Page3:Classbasi
UVA - CS - 101
Suppose String variable TOWN_DATABASE has already been defined. The String represents the name of the web page. Define a URL variable that represents that web page. Define a Scanner named reader that reads from that URL. Define a HashMap variable
UVA - CS - 101
CS101XSpring2008Name_EMAILID_ This pledged exam is open textbook and notes. Because the questions have different point amounts, be sure to look over the entire exam and plan your time accordingly. PLEDGE:Page 2 _ / 8 Page 3 _ / 32 Page 4 _ / 30 Pag
UVA - CS - 101
CS101X Spring 2007 Test 3NameEmail IDThis pledged exam is open text and open-notes. You may use the web to look up information on the Java language but you may not search for Java files. You may not access your home directory or files that you
UVA - CS - 101
CS 101 Spring 2007 Midterm 2: Name: _Email ID: _ This pledged exam is open text book but open-notes, closed-calculator, closed-neighbor, etc. Questions are worth different amounts, so be sure to look over all the questions and plan your time accordin
UVA - CS - 101
CS 101 Spring 2007 Name _ Section _Email ID _This pledged exam is open text book. You may also JCreator on your computer. You may not use JCreator on any existing files or examples; i.e., you can only use it to create new files. You may also acce
UVA - CS - 101
CS101XSpring2008Name_EMAILID_ This pledged exam is open textbook and notes. You may also JCreator, Eclipse, or Dr Java on the last question. Because the questions have different point amounts, be sure to look over the entire exam and plan your time a
UVA - CS - 101
CS101XSpring2008Name_EMAILID_ Thispledgedexamisopentextbook,cribsheet,andtwopagesofnotes.Itisclosedcalculator,computer,and neighbor. Pledge: Page3:Methodbasics Page4:Parameterpassingandreturnbasics Page5:Arraybasics Page6:Collectionbas
UVA - CS - 101
CS101XSpring2008Name_EMAILID_ This pledged exam is open text and notes. Because questions have different point amounts, look over the entire exam and plan your time accordingly. PLEDGE:1. ( 5 points): True or False Youappearintheclasspicture
UVA - CS - 101
CS 101 Spring 2006 Midterm 1Name: _Email ID: _1. GivethetypeandvalueofeachofthefollowinglegalJavaexpressions.Thefirst oneisdoneforyou. Expression(a) (b) (c) (d) (e) (f) (g) (h) (i) 1 + 2 9 % 4 &quot;Strength&quot; + &quot;s&quot; &quot;1&quot; + &quot;2&quot; 5 &lt; 2 5 / 3 1.0 / 10.0
UVA - CS - 101
C101X BeginningofCourseMemorandum Thefuturebelongstothosewhobelieveinthebeautyoftheirdream. EleanorRoosevelt Ilikethedreamsofthefuturebetterthanthehistoryofthepass. ThomasJefferson Wantwhatyoudo JimCohoonPrerequisites Objectives Nopriorprogr
Maryville MO - GAOY - 121306
Maryville MO - CS - 7010
PROFILES AND FUZZY K-NEAREST NEIGHBOR ALGORITHM FOR PROTEIN SECONDARY STRUCTURE PREDICTIONRAJKUMAR BONDUGULA, OGNEN DUZLEVSKI, AND DONG XU * Digital Biology Laboratory, Department of Computer Science, University of Missouri-Columbia Columbia, MO 652
Maryville MO - CS - 303
1. What is the number of basic steps executed by the following method (as a function of n)? What is the time complexity of the method? Public int howLongA(int n) { int k = 0, kk = 0; for(int i = 0; i &lt; n/2 ; i+) { k+; for(int j = 0; j &lt; n/2; j+) kk+;
Maryville MO - CS - 303
Lecture Outline (CS 303, Dong Xu, 2/13/04)Things to startQuiz on 2/16, get familiar with pseudocode. Other questions?OutlineReview on maintaining the heap property (6.2) Building a heap (6.3) Heapsort (6.4) Priority queues (6.5) Maintaining he
Maryville MO - CS - 303
Lecture Outline (CS 303, Dong Xu, 2/4/04)Things to start.lg *(n) CS 303 Mailing list Send an email to LISTSERV@po.missouri.edu. Place a statement in the body of the email (not on the Subject line): subscribe CECS303-L Joe User Rules for the quizzes
Maryville MO - CS - 303
Lecture Outline (CS 303, Dong Xu, 1/28/04)Things to start.Quiz Coverage of quiz (only things discussed in the lectures) Please read textbook and do homework! Questions from last lecture?OutlineAsymptotic notation (3.1) Standard notation and comm
Maryville MO - CS - 303
Lecture Outline (CS 303, Dong Xu, 2/25/04)Things to start.Discussion on the quiz Other questions?OutlineLower bounds for sorting (8.1) Counting sort (8.2) Lower bounds for sorting Lower bounds Comparison sort and decision tree Lower bound
Maryville MO - CS - 303
Lecture Outline (CS 303, Dong Xu, 2/20/04)Things to startMidterm Other questions?OutlineA randomized version of quicksort (7.3) Analysis of quicksort (7.4) Review on performance of quicksort Balanced Intuition for average case A randomized
Maryville MO - PT - 316
The Integumentary SystemRepair and Management: An OverviewJoseph McCulloch, PT, PhD, FAPTA ObjectivesAfter reading this article, you should be able to: Explain the physiological events related to wound repair (inflammation, proliferation, maturatio
Maryville MO - AE - 4972
First Editionw w w. s t o e l . c o mCooperaTivesBusiness, structure, and Legal issuesThe Law ofCompliments ofTa b l e o f C o n t e n t sCoopEraTivEsBusiness, structure and Legal issuesThe Law of1. Legal Framework of Cooperative De
UVA - CS - 150
CS150: Problem Set 3: L-System FractalsPage 1 of 15University of Virginia, Department of Computer Science cs150: Computer Science Spring 2007Problem Set 3: L-System FractalsCollaboration Policy - Read CarefullyOut: 5 February 2007 Due: Mond
UVA - CS - 751
A History-Based Test Prioritization Technique for Regression Testing in Resource Constrained EnvironmentsJung-Min Kim Adam Porter Department of Computer Science University of Maryland, College Park College Park, MD 20742, USA +1-301-405-2702 {jmkim,
UVA - CS - 751
Static Coverage Prediction for Regression TestGuangyu Dong Jia Xu Yuanyuan SongOutlineProblem Solution Evaluation Conclusion Q&amp;AProblemRegression test is important but expensive Two factors might be helpful to improve the performance of regres
UVA - CS - 751
Coverage Prediction Based on Invoking RelationsA facility for prioritizing regression testYuanyuan Song Guangyu Dong Jia XuOur current goalNarrowed, compared to what we have claimed in the proposal Is to find an effective and practical algorithm
UVA - CS - 751
A Study of Effective Regression Testing in PracticeW. Eric Wong, J. R. Horgan, Saul London, Hira Agrawal Bell Communications Research 445 South Street Morristown, NJ 07960AbstractThe purpose of regression testing is to ensure that changes made to
UVA - CS - 751
Proceedings of the International Conference on Software Maintenance, Oxford, UK, September, 1999, IEEE CopyrightTest Case Prioritization: An Empirical StudyGregg RothermelDepartment of Computer Science Oregon State U. Corvallis, OR grother@cs.ors
UVA - CS - 751
Effectively Prioritizing Tests in Development EnvironmentAmitabh SrivastavaMicrosoft Research One Microsoft Way Redmond, WAJay ThiagarajanMicrosoft Research One Microsoft Way Redmond, WAamitabhs@microsoft.com ABSTRACTSoftware testing helps en
UVA - CS - 751
IEEE Transactions on Software Engineering (to appear).Prioritizing Test Cases For Regression TestingGregg RothermelDepartment of Computer Science Oregon State U. Corvallis, OR grother@cs.orst.eduRoland H. UntchDepartment of Computer Science Mi
UVA - CS - 656
9 6 5 (7(y t&quot; E )AB e b eG 4 &quot; pT &amp; &quot; 1 (9U F&quot; Ace G q@% 7&quot; V ! d 3 4 G Q E E 9 w w Q &amp; ! R x 5b 5b 6 5 y y x G w u B B FE&quot; )s ! &quot; &quot; 3 c dB 3 #0 &quot; ix 9 c!Q %9 B p EF&quot; &quot; &amp; YG E 7gDg8b F(
UVA - CS - 751
The Impact of Test Suite Granularity on the Cost-Effectiveness of Regression TestingGregg Rothermel , Sebastian Elbaum , Alexey Malishevsky , Praveen Kallakuri , Brian Davia Department of Computer Science Oregon State University Corvallis, Or
UVA - CS - 751
Static Coverage Prediction for Regression TestGuangyu Dong gd4j@cs.virginia.edu ABSTRACTIn this paper, we describe a novel method to predict coverage information on modified code, which is helpful for test cases selection in regression test. We int
UVA - CS - 656
Fault tolerance in the entity maintenance and group management for sensor networksWei Le wl3t@cs.virginia.edu Jia Xu jx9n@cs.virginia.edu Hong Xu hx5s@virginia.eduAbstractIn this paper, we analyze the impact of the node failure on the entity main
UVA - CS - 202
TEST 3 CS/APMA 202Name:_This exam is closed book and closed notes. You may not consult any notes, textbooks, homeworks, or other materials. Calculators and other calculating devices are prohibited. (14) 1. A drawer contains 10 red socks, 10 blue
Maryville MO - STAT - 9100
Stat 9100.3: Analysis of Complex Survey Data1LogisticsInstructor: Stas Kolenikov, kolenikovs@missouri.edu Class period: MWF 1-1:50pm Ofce hours: Middlebush 307A, times: TBA Website: Blackboard http:/courses.missouri.edu Information: This course
Maryville MO - PT - 8690
Effects of neurodevelopmental treatment (NDT) for cerebral palsy: an AACPDM evidence reportWritten by Charlene Butler* EdD Johanna Darrah PhD Approved by AACPDM Treatment Outcomes Committee Review Panel: Richard Adams MD Henry Chambers MD Mark Abel
Maryville MO - BE - 470
BE 8380 Project I Numerical Simulation 1. Implement the Runge-Kutta scheme in a computer language of your choice. The equations to be solved by the algorithm are in the form of first-order ODE's. They are linear or nonlinear, less than 10th order, an
Maryville MO - BE - 470
BE 8380 Project III Process IdentificationAssume that a real process obeys the following differential equation:&amp; + 6 y + 5 y = 5u &amp; ywhere y(t) is the process output and u(t) is the process input. 1. Use a step response to estimate the frequency
Maryville MO - BE - 470
BE 8380 Project IV Neural Network Pattern Recognition Neural networks can be used to model virtually any relationships between two sets of variables. It is especially useful for representing complex, nonlinear, multipleinput and multiple-output relat
Maryville MO - BE - 470
BE 8380 Project II Application of Bond Graph Modeling in Analysis of Viscoelastic and Dielectric Behaviors In the bond graph approach, system components are categorized and represented as several multi-port elements. While these elements appear to be
Maryville MO - BE - 315
LAB REPORT STYLE BE 315Lab reports should be prepared according to the following style. Introduction This should be a brief statement about a lab exercise. State why the lab was done and what the lab objectives were. Procedures and Results This par
Maryville MO - ECE - 4270
Maryville MO - PHYS - 215
Physics 215 Winter 2002Introduction to Modern PhysicsProf. Ioan Kosztin Lecture #25Solid State Physics Bonding in solids (metals, isolators, semiconductors) Classical free electron theory of metals Quantum theory of metals Band theory of so