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Minnesota - CH - 5021
# File ex13_012.txt from publisher's web site# Data for Ex. 13.12, p. 820 of IPS4# Col. 1: id = group number (1-6)# Col. 2: gender (factor, 1=Females, 2=Males)# Col. 3: major (factor, 1=CS, 2=EO, 3=O)# Col. 4: grades = mean high school math grad
Minnesota - CH - 5021
# File ex12_013.txt from publisher's web site# Data for Ex. 12.13, p. 784 of IPS4# Col. 1: id = case number (1-10)# Col. 2: time = days after baking# Col. 3: vitamina = Vitamin A content (mg/100 g)# Col. 4: vitamine = Vitamin E content (mg/100 g
Minnesota - CH - 5021
# File ex12_021.txt from publisher's web site# Data for Ex. 12.21, p. 786 of IPS4# Col. 1: id = infant number (1-45)# Col. 2: bftime (factor, 1=BF4, 2=BF5, 3=BF6, months)# Col. 3: energy = energy intake, (kcal/d) id bftime energy 1 BF4 499
Minnesota - CH - 5021
# File ex11_051.txt from publisher's web site# Data for Ex. 11.51, p. 743 of IPS4 (Table 10.1, p. 694)# Col. 1: id = woman number (1-60)# Col. 2: wages = proportional to weekly wages# Col. 3: los = length of service (months)# Col. 4: size = ban
Minnesota - STAT - 5931
cross$ export LD_LIBRARY_PATH=/APPS/ggobi/libcross$ R> library("Rggobi")>> data(mtcars)>> class(mtcars)[1] "data.frame"> names(mtcars) [1] "mpg" "cyl" "disp" "hp" "drat" "wt" "qsec" "vs" "am" "gear"[11] "carb"> help(mtcars)> gg
Minnesota - STAT - 5303
Stat 5303Designing ExperimentsFall Semester 2007Time: Location: Textbook: Web page: Instructor:10:10 a.m. to 11:00 a.m. on Mondays, Wednesdays, and Fridays Ford 115 A First Course in Design and Analysis of Experiments by Oehlert http:/www.sta
Minnesota - STAT - 3022
zip fire theft age income race vol invol26 6.2 29 60.4 11744 10 5.3 040 9.5 44 76.5 9323 22.2 3.1 0.113 10.5 36 73.5 9948 19.6 4.8 1.257 7.7 37 66.9 10656 17.3 5.7 0.5
Minnesota - STAT - 3022
jnt1 jnt2 species191 131 conc185 134 conc200 137 conc173 127 conc171 118 conc160 118 conc188 134 conc186 129 conc174 131 conc163 115 conc190 143 conc174 131 conc
Minnesota - STAT - 3022
zinc code185 1189 1187 1181 1150 1176 1171 2174 2202 2171 2207 2125 2189 2179 2163 2174 2184 2186 2210 3139 3172 3198 3177 3
Minnesota - STAT - 3022
temp failure53 156 157 163 066 067 067 067 068 069 070 070 170 170 172 073 075 075 176 076 078 079 080 081
Minnesota - STAT - 3022
absent machine-841 -1375-436 -599-224 -129160 47597 7132-356 1116300 940288 987609 1927412 2150167 2573364 2620384 3596320 3619240 41951365 4395392 4512404 5088408
Minnesota - STAT - 3022
carbonat calcite21.3 20.523.6 23.226.7 27.026.8 28.727.0 27.927.1 27.927.2 29.027.3 27.727.5 27.627.6 29.628.0 28.028.0 29.228.2 27.529.3 28.429.4 28.529.4 29.329.4 30.029.5 31.0
Minnesota - STAT - 3022
absentee machines-841 -1375-436 -599-224 -129160 47597 7132-356 1116300 940288 987609 1927412 2150168 2573364 2620384 3596320 3619240 41951365 4395392 4512404 50884
Minnesota - STAT - 3022
planet order distance Mercury 1 3.87 Venus 2 7.23 Earth 3 10.00 Mars 4 15.24 Asteroids 5 29.00 Jupiter 6 52.03 Saturn 7 95.46 Uranus 8 192.00 Neptune 9 300.90 Pluto 10 395.00
Minnesota - STAT - 3022
brain liver time treat days sex weight loss tumor41081 1456164 .5 BD 10 F 239 5.9 22144286 1602171 .5 BD 10 F 225 4 246102926 1601936 .5 BD 10 F 224 -4.9
Minnesota - STAT - 3022
area species44218 10029371 1084244 453435 5332 165 111 7
Minnesota - STAT - 3022
context mode level m percent1 1 1 132 20.5 2 1 1 132 31.11 1 2 132 28.02 1 2 131 38.91 2 1 132 34.12 2 1 131 48.91 2 2 132 23.52 2 2 123 45.5
Minnesota - STAT - 3022
company treat score1 1 80.01 2 63.21 2 69.22 1 83.92 2 63.12 2 81.53 1 68.23 2 76.24 1 76.54 2 59.54 2 73.5
Minnesota - STAT - 3022
time voltage code5.79 26 11579.52 26 12323.7 26 168.85 28 2108.29 28 2110.29 28 2426.07 28 21067.6 28 27.74 30 317.05 30 320.46 30 321.02 30 322.66 30 343.4 30 347.3 30 3139.07 30 3144.12 30 3175.88 30 3194.9 30 30.27 32 40.4 32
Minnesota - STAT - 5931
> n <- 300> x <- runif(n)> y <- runif(n)> plot(x, y)> plot(x, y, asp = 1)> lines(c(0, 1, 1, 0, 0), c(0, 0, 1, 1, 0)> plot(x, y, asp = 1, type = "n", axes = FALSE, xlab = ", ylab = ")> lines(c(0, 1, 1, 0, 0), c(0, 0, 1, 1, 0)> points(x, y)>
Minnesota - CH - 5021
# File ex08_066.txt from publisher's web site# Data for Ex. 8.66, p. 603 of IPS4# Col. 1: text = text number (1-10)# Col. 2: girl = number of usages of "girl"# Col. 3: woman = number of usages of "woman"# Col. 4: boy = number of usages of "boy"
Minnesota - CH - 5021
# File ex10_044.txt from publisher's web site# Data for Ex. 10.44, p. 705 of IPS4# Col. 1: id = perch number (1-12)# Col. 2: weight = fish weigh (g)# Col. 3: len = fish length (cm)# Col. 4: width = fish width (cm)perch weight len width 1
Minnesota - CH - 5021
# File ta02_009.txt from publisher's web site# Data from Table 2.9, p. 161 of IPS4# Col. 1: child = child number (1 - 21)# Col. 2: age = age of child (months)# Col. 3: score = Gesell score of childchild age score 1 15 95 2 26 71
Minnesota - CH - 5021
# File ex10_004.txt from publisher's web site# Data for Ex. 10.4, p. 692 of IPS4# Col. 1: id = student number (1-16)# Col. 2: beers = number of cans of beer# Col. 3: bac = blood alcohol content id beers bac 1 5 0.100 2 2 0.030 3
Minnesota - CH - 5021
# File ex09_032.txt from publisher's web site# Data for Ex. 9.32, p. 647 of IPS4# Col. 1: responded (factor, 1=no, 2=yes)# Col. 2: letter (factor, 1=letter, 2=none)# Col. 3: count = number of physicians in cell# Note: cell number column dropped
Minnesota - CH - 5021
# File ex07_058.txt from publisher's web site# Data for Ex. 7.58, p. 544 of IPS4# Col. 1: apt = apartment number# Col. 2: rooms = number of rooms (1 or 2)# Col. 3: rent = rent ($/mo)apt rooms rent 1 2 595 2 2 500 3 2 580
Minnesota - CH - 5021
# File ex07_060.txt from publisher's web site# Data for Ex. 7.60, p. 545 of IPS4# Col. 1: loaf = loaf number (1-4)# Col. 2: days = days stored# Col. 3: vitaminc = vitamin C content (mg/100 g)loaf days vitaminc 1 0 47.62 2 0 49.79
Minnesota - CH - 5021
# File ex09_035.txt from publisher's web site# Data for Ex. 9.35, p. 648 of IPS4# Col. 1: current (factor 1=thislose, 2=thiswin)# Col. 2: next (factor (1=nextlose, 2=nextwin)# Col. 3: funds = number of stock funds# Note: cell number column dropp
Minnesota - CH - 5021
# File ex09_020.txt from publisher's web site# Data for Ex. 9.20, p. 643 of IPS4# Col. 1: wine (factor, 1=French, 2=Italian, 3=Other)# Col. 2: music (factor, 1=French, 2=Italian, 3=None)# Col. 3: count = number of purchases in cell# Note: cell n
Minnesota - CH - 5021
# File ex10_037.txt from publisher's web site# Data for Ex. 10.37, p. 702 of IPS4# Col. 1: id = specimen number (1-5)# Col. 2: femur = length of femur (cm)# Col. 3: humerus = length of humerus (cm) id femur humerus 1 38 41 2 56 63 3
Minnesota - HAWKI - 068
THE COMMUNITY-ENGAGED SCHOLARSHIP FOR HEALTH COLLABORATIVE Many untenured faculty find they must choose between `doing the work that would contribute to career advancement' and doing the work of the institution in linking with communities and educati
Minnesota - NRESEXOTIC - 3002
Biological Invasions:Increasing - Great Lakes, Atlantic & Pacific Bays, Terrestrial, etc.Invasion Process Transport Introduction Establishment rapid growth, integration Spread Impact system Natural declines or stabilization? more rapid with less d
Minnesota - NRESEXOTIC - 3002
Biological Invasions:Increasing - Great Lakes, Atlantic & Pacic Bays, Terrestrial, etc.Invasion Process Transport Introduction Establishment rapid growth, integration Spread Impact system Natural declines or stabilization? more rapid with less dis
Minnesota - FW - 8459
FW 8459 STREAM and RIVER ECOLOGYFall 2000General Phylogenetic/Taxonomy of Some Important Stream Organisms This is an incomplete and biased list but illustrates some key organisms along with their classification.- classifications have been changin
Minnesota - FW - 8459
FW 8459 Stream and River Ecology Nutrient and Carbon Spiraling Relations/EquationsFall 2008The below equations outline some key relations in nutrient and carbon spiraling. Consult the below refs for more information. Note that because the beginni
Minnesota - FW - 5604
2006 SPRING/SUMMER INTERNSHIPMNDNR-LAKE SUPERIOR FISHERIESThe purpose of this position is to assist the Lake Superior management team in the sampling and analysis of fisheries data collected from stocks in Lake Superior and its tributary streams.
Minnesota - PHYS - 1063
Keywords Wednesday, September 19, 2007 Electromagnetic radiation Blackbody radiation Wavelength Intensity Stefan-Boltzmann law Wiens law Colors and wave lengths Light Infrared light Visible light Ultraviolet light Long-wave radiation Short-wave radia
Maryland - MATH - 115
Math 115 Exam 2 Sample 2 1. Suppose a(x) = x + 3 and suppose b(x) is an unknown function with b(3) = 5, b(1) = 6 and b(0) = 4. Find each of the following: (a) (a b)(1). (c) (a + b)(3)(b) (b a)(3) 2. Determine the average rate of change of h(x) =
Minnesota - CE - 5214
Simulator of Network Growth (SONG 1.0) for Homework 4 APrepared for Homework 4A, CE 5214 April 13, 2004What is Simulation?DefinitionlDynamic representation of some part of the real world through building computer model and moving it through
U. Memphis - COMP - 7120
Chapter 7: Signature SchemesCOMP 7120-8120 Lih-Yuan Deng lihdeng@memphis.eduOverviewIntroduction Security requirements for signature schemes ElGamal signature scheme Variants of ElGamal signature schemeDSA: Digital Signature AlgorithmProvably
U. Memphis - UNHP - 4453
How Minds WorkSparse Distributed MemoryStan FranklinComputer Science Division & Institute for Intelligent Systems The University of Memphis1Boolean Geometry The geometry of Boolean space Boolean space of dimension n- the set of all Boolean
U. Memphis - CS - 6740
Single and Multilayer Perceptrons I. The perceptron learning rule is a special case of the general learning rule: Wji = Wji + c*r*xj where: Wji is the synaptic weight from the jth neuron to neuron ith, c is the learning rate, r is the learning signal
U. Memphis - CS - 6601
Efficiency and Reliability of Semantic Retrieval in DNA-based MemoriesMax H. Garzon1, Kiran Bobba1, Andrew Neel11Computer Science, The University of Memphismgarzon@memphis.eduAssociative memories based on DNA-affinity have been proposed. Here
U. Memphis - UNHP - 4453
How Minds WorkMinds, Agents, Senses, ActionsStan FranklinComputer Science Division & Institute for Intelligent Systems The University of Memphis1Two Burning Questions for Me How do minds work? Human minds Animal minds Artificial Minds H
U. Memphis - UNHP - 4453
How Minds WorkIDA and her ArchitectureStan FranklinComputer Science Division & Institute for Intelligent Systems The University of Memphis1Who is IDA? IDA is an intelligent, autonomous software agent that does personnel work for the US Navy
U. Memphis - UNHP - 4453
How Minds WorkBrains, Ontologies & Virtual MachinesStan FranklinComputer Science Division & Institute for Intelligent Systems The University of Memphis1Question: How do minds work? What would an answer be like? That depends on the level of gr
U. Memphis - UNHP - 4453
How Minds WorkTools for Thinking about Minds: An Ontology for CognitionStan FranklinComputer Science Division & Institute for Intelligent Systems The University of Memphis1Ontology? Philosophythe study of the nature and relations of being C
U. Memphis - UNHP - 4453
How Minds WorkNeuroscienceStan FranklinComputer Science Division & Institute for Intelligent Systems The University of Memphis1Nervous Systems Wetware underlying minds in animals Control sense-process-act cycles Composed of Neurons Gangli
U. Memphis - CS - 7272
Biomolecular Computing in silicoMax H. Garzon Computer Science The University of Memphis0.2Jump to first pageAdleman's Example: HPP/TSPJump to first pageEncoding`GCATGGCC 0 CCGGTCGA' CCGGTACC' 2 `ATGGCATG 0 1 0 2 `GCATGGCCATGGCATG CCGGTACC
U. Memphis - CS - 7272
COMP7272ParallelandDistributedComputingConnectionMachinesMaxH.Garzon ComputerScience TheUniversityofMemphis0.2Jump to first pageCONNECTION MACHINE (CM-2)s sFine-grained massively data parallel processor with 16K, 32K, 64K PEs Languages:
U. Memphis - UNHP - 4453
How Minds WorkBehavior NetsStan FranklinComputer Science Division & Institute for Intelligent Systems The University of Memphis1Desired Characteristics Goal oriented Opportunistic Persistent Able to plan ahead Robust Reactive Fast Not
U. Memphis - CS - 7272
Parallel Programming: Distributed SystemsOctober 7, 2002 Characterization of Distribute Systems"A distributed system is one in which components located at networked computers communicate and coordinate their actions only by passing m
U. Memphis - UNHP - 4453
How Minds WorkSchema MechanismStan FranklinComputer Science Division & Institute for Intelligent Systems The University of Memphis1Schema Mechanism Implements early stages of Piaget's theory of child development A mechanism of mind Control
U. Memphis - CS - 7745
COMPUTATIONAL INTELLIGENCE COMP 7745/8745, Fall 2004Lab 4: Fuzzy Implication Methods6 October 2004Implication methods in FIS Mamdani MaxMin: Larsen MaxProduct: A ( x) B ( y) A ( x) B ( y)Both of these are implemented in standard Ma
U. Memphis - CS - 7517
Topics in Human Computer Interaction Chapter 3: The Interaction1. What is an encompassing model of interaction in HCI? Why is a model useful?2. In what sense is the interaction problem solving? A mapping? A cycle?3. What are the main gulfs in i
U. Memphis - COMP - 7120
7120-8120. Cryptography and Data Security Spring, 2008Lih-Yuan Deng Contact Information:Office: 359 Dunn Hall Phone: 678-3134 E-mail: lihdeng@memphis.edu Department Office: 209 Dunn Hall Department Phone: 678-5465Office Hours:Monday Tuesday 9:30
U. Memphis - CS - 7100
WebServicesHongjunSong ComputerScience TheUniversityofMemphisCOMP7100:ComputersintheInformationsociety1What is a Web Service? A web service is a collection of protocols and standards used for exchanging data between applications or systems. S
U. Memphis - CS - 3160
Tentative Lecture ScheduleThe following list is the tentative lecture schedule subjecting to changes when it becomes necessary. Date June 4 June 6 June 11 June 13 June 18 June 20 June 25 June 27 July 2 July 9 July 11 July 16 July 18 July 23 July 25
U. Memphis - CS - 3160
Advanced Data and File Structures COMP 3160Fall 2003Instructor Information Hongjun Song, Ph.D. Office: Dunn Hall Office Hours: By Appt. Course Description COMP 3160 is the third course in the Computer Science program. In this course, we will revi
U. Memphis - CS - 46014
Tentative Lecture ScheduleThe following list is the tentative lecture schedule subjecting to changes when it becomes necessary. Date 6/10 Lecture Topics Introduction to the Internet and the Web: Architecture and Models Introduction to Java Applica
U. Memphis - CS - 46302
Tentative Lecture ScheduleThe following list is the tentative lecture schedule subjecting to changes when it becomes necessary. Date 1/21 1/23 1/28 1/30 2/4 2/6 2/11 2/13 2/18 2/20 2/25 2/27 3/4 3/6 3/11 3/13 3/18 3/20 3/25 3/27 4/1 4/3 4/8 4/10 4/1