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Wisconsin - PHIL - 101
Victoria Yakovleva Philosophy 101 Professor Shapiro 23 October 2006In Rene Descartes' first and second meditations, Descartes attempts to peel back his preconceived opinions in order to discover certain and unquestionable knowledge. According to De
Wisconsin - ZOO - 151
Discussion questions for week 4: 1. Describe the structure of the cell membrane. Explain how its structure is related to its functions. 2. Compare and contrast the various types of transport across the cell membrane. 3. A cell whose cytoplasm consist
Wisconsin - ZOO - 151
Discussion questions for week 2: 1. Lipids are non-polar molecules. Explain why lipids could not support life as we know it. 2. Describe the structures and functions of starch and cellulose. What are the similarities and differences between the two c
Wisconsin - ZOO - 151
Discussion questions for week 5: 1) What is the function of an enzyme? How does an enzyme interact with its substrate? 2) Describe the different types of inhibition. Your answer should include competitive, non-competitive, feedback, and allosteric in
Wisconsin - SPANISH - 204
El gaucho: visitar un sitio web - Composicin informalEste fin de semana, Ud. va a explorar un sitio web sobre la cultura del gaucho, una figura importante en el cuento El sur de Jorge Luis Borges. Hay mucha informacin en este sitio; entonces Ud. va
Wisconsin - PHIL - 101
Victoria Yakovleva Philosophy 101 Professor Shapiro 18 September 2006In David Hume's Dialogues Concerning Natural Religion, Part II, the characters of Demea, Philo, and Cleanthes discuss the nature of God. After Demea and Philo concur that the bein
Wisconsin - SPANISH - 204
Victoria Yakovleva Espaol 204 15 Diciembre 2006La historia oficial En esta pelcula, Alicia Ibez es una maestra de historia en el escuela secundaria en Buenos Aires. Desde el principio, es evidente que Alicia tiene un enfoque muy estricto sobre cmo
Wisconsin - PHIL - 101
Victoria Yakovleva Philosophy 101 Professor Shapiro 06 November 2006In "The Qualia Problem," Frank Jackson discusses the philosophy of mind. He states that there is more to conscious experience than just physical information. He believes that even
Wisconsin - PHIL - 101
Victoria Yakovleva Philosophy 101 Professor Shapiro 20 November 2006In "Minds, Brains, and Programs," John R. Searle argues against the claim of strong artificial intelligence, particularly against the claim that a programmed computer can understan
Wisconsin - STAT - 324
Statistics 324 Discussion 311 w/ Jack Homework 1 - Victoria Yakovleva The hellung data frame has 51 rows and 3 columns. Diameter and concentration of Tetrahymena cells, with and without glucose added to growth medium. This data frame contains the fo
Wisconsin - STAT - 324
Statistics 324 Discussion 311 w/ Jack Homework 2 Victoria Yakovleva 1. die1 <- sample(1:6, 120, replace = TRUE) xtabs(~ die1) die1 1 2 3 4 5 6 20 21 21 21 20 17 barchart(xtabs(~ die1)If the outcomes (1-6) are equally likely, the results should be
Wisconsin - STAT - 324
Statistics 324 Discussion 311 w/ Jack Homework 3 Victoria Yakovleva 1. xvals<-seq(from=-3, to=3, by=0.01) p<-pnorm(xvals) xyplot(p~xvals,type=c("l","g")The cumulative distribution function is a continuous, increasing, sigmoidal shaped function th
Wisconsin - STAT - 324
Statistics 324 Discussion 311 w/ Jack Homework 4 Victoria Yakovleva 1. mn <- replicate(50000, mean(rnorm(4, mean = 100, sd = 20) mean(mn) [1] 99.99353 This is close to =100. var(mn) [1] 100.7322 The theoretical variance of the sample mean of sample
Wisconsin - STAT - 324
Statistics 324 Discussion 311 w/ Jack Homework 5 Victoria Yakovleva 1. SAMPLE SIZE = 5 mean(theo) [1] -0.001448658 stand <- (mean(rnorm(n, m = 100, sd = sd)-(100)/(sd/sqrt(n) stand [1] 0.5469978This standardized sample mean appears to have a norm
Wisconsin - STAT - 324
Statistics 324 Discussion 311 w/ Jack Homework 6 Victoria Yakovleva 1. with(vitcap, t.test(vital.capacity~group, conf.level=0.99) Welch Two Sample t-test data: vital.capacity by group t = -2.9228, df = 19.019, p-value = 0.008724 alternative hypothe
Wisconsin - STAT - 324
Statistics 324 Discussion 311 w/ Jack Homework 7 Victoria Yakovleva 1. xyplot(body.weight~metabolic.rate,data = rmr,type=c("g","p","smooth")According to this graph, a simple linear regression model doesn't seem reasonable. xyplot(body.weight~meta
UT Arlington - INSY - 3300
Lab 4 Some TCP/IP UtilitiesDue on March 5th Using any Windows XP workstation with internet connection that is accessible to you (e.g., your own computer or university computer at libraries), please finish the following task individually.Objective
UT Arlington - INSY - 3300
Alice in Action with JavaChapter 1 Getting Started with AliceObjectives Design a simple Alice program Build a simple Alice program Animate Alice objects by sending them messages Use the Alice doInOrder and doTogether controlsAlice in Action
UT Arlington - INSY - 3300
Alice in Action with JavaChapter 2 MethodsObjectives Build world-level methods to help organize a story into scenes and shots Build class-level methods to elicit desirable behaviors from objects Reuse a class-level method in multiple worlds U
UT Arlington - INSY - 3300
Alice in Action with JavaChapter 3 Variables and FunctionsObjectives Use variables to store values for use later in a method Use a variable to store the value of an arithmetic expression Use a variable to store the value produced by a function
UT Arlington - INSY - 3300
Alice in Action with JavaChapter 4 Flow ControlObjectives Use the Boolean type and its basic operations Use the if statement to perform some statements while skipping others Use the for and while statements to perform (other) statements more t
UT Arlington - INSY - 3300
Alice in Action with JavaChapter 7 From Alice to JavaObjectives Write some first Java programs Learn the basics of the Eclipse Integrated Development Environment (IDE) Begin making the transition from Alice to JavaAlice in Action with Java
UT Arlington - INSY - 3300
Alice in Action with JavaChapter 8 Types and ExpressionsObjectives Use variables and constants Understand the difference between Javas fundamental and class types Build complex Java expressions Better understand and use Javas Scanner and Prin
UT Arlington - INSY - 3300
Alice in Action with JavaChapter 9 MethodsObjectives Build your own Java methods Define parameters and pass arguments to them Distinguish between class and instance methods Build a method libraryAlice in Action with Java2Methods How to
UT Arlington - INSY - 3300
Alice in Action with JavaChapter 10 Flow Control in JavaObjectives Learn how to use the if statement Learn how to use the switch statement Learn how to use the while loop Learn how to use the for loop Learn how to use the do loopAlice in A
UT Arlington - INSY - 3300
Alice in Action with JavaChapter 11 Files and ExceptionsObjectives Open and close text files Read values from, and write values to, text files Catch, handle, and throw exceptionsAlice in Action with Java2Files and Exceptions Main topics
UT Arlington - INSY - 3300
Alice in Action with JavaChapter 12 Arrays and Lists in JavaObjectives Understand Java's array data structure Solve problems using Java's LinkedList data structure Solve problems using Java's ArrayList data structureAlice in Action with Java
UT Arlington - INSY - 3300
Alice in Action with JavaChapter 13 Object-Oriented ProgrammingObjectives Design and build class hierarchies Understand inheritance and polymorphism Override inherited methods Build abstract classesAlice in Action with Java2Object-Orien