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.

DECISION MAKING AND RELEVANT INFORMATION By :Dr. Suyanto, SE, MM, M.Ak Email : suyanto@cbn.net.id TRUE/FALSE 1. A decision model is a formal method for making a choice, frequently involving both quantitative and qualitative analyses. Answer : True Difficulty : 1 Objective : 1 Terms to Learn : decision model, quantitative factors, qualitative factors 2. Feedback from previous decisions uses historical information and, therefore, is irrelevant for making future predictions. Answer : False Difficulty : 2 Objective : 1 Terms to Learn : relevant costs Historical costs may be helpful in making future predictions, but are not relevant costs for decision making. 3. The amount paid to purchase tools last month is an example of a sunk cost. Answer : True Difficulty : 2 Objective : 2 Terms to Learn : sunk costs 4. For decision making, differential costs assist in choosing between alternatives. Answer : True Difficulty : 1 Objective : 2 Terms to Learn : differential cost 5. For a particular decision, differential revenues and differential costs are always

**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:

LSU - ACCT - 4121

CHAPTER 13 STRATEGY, BALANCED SCORECARD, AND STRATEGIC PROFITABILITY ANALYSISTRUE/FALSE 1. Strategy describes how an organization matches its own capabilities with the opportunities in the marketplace to accomplish its overall objectives. Answer: Terms t

LSU - ACCT - 4121

CHAPTER 20 INVENTORY MANAGEMENT, JUST-IN-TIME, AND SIMPLIFIED COSTING METHODSTRUE/FALSE 1. Retailers generally have a high percentage of net income to revenues. Answer: False Difficulty: 2 Terms to Learn: inventory management Retailers have a low percent

LSU - ACCT - 4121

CHAPTER 21 CAPITAL BUDGETING AND COST ANALYSISTRUE/FALSE 1. Capital budgeting focuses on projects over their entire lives to consider all the cash flows or cash savings from investing in a single project. Answer: Terms to Learn: 2. True Difficulty: capit

LSU - ACCT - 4121

CHAPTER 22 MANAGEMENT CONTROL SYSTEMS, TRANSFER PRICING, AND MULTINATIONAL CONSIDERATIONSTRUE/FALSE 1. The goal of a management control system is to improve the collective decisions in an organization in an economically feasible way. Answer: Terms to Lea

LSU - ACCT - 4121

CHAPTER 23 PERFORMANCE MEASUREMENT, COMPENSATION, AND MULTINATIONAL CONSIDERATIONSTRUE/FALSE 1. Many common performance measures, such as customer satisfaction, rely on internal financial accounting information. Answer: False Difficulty: 1 Objective: 1 T

VCU - MATH - 532

Guide to Commonly Used NotationSymbol R Rn t u, v x, y x0 , y0 x , y f A, M, P D N tr( A) det( A) , Es , Eu , Ec Ws, Wu, Wc AB spancfw_v1 , v2 , . . . vn t (x0 ) t f : Rn Rm f Jf uv v 2 u-v 2 B(x, ) V (x) (t)Usual Meaning the set of real numbers n-dime

VCU - MATH - 532

Ordinary and Partial Differential EquationsAn Introduction to Dynamical SystemsJohn W. Cain, Ph.D. and Angela M. Reynolds, Ph.D.Mathematics Textbook Series. Editor: Lon Mitchell 1. Book of Proof by Richard Hammack 2. Linear Algebra by Jim Hefferon 3. A

VCU - MATH - 532

CHAPTER 1 IntroductionThe mathematical sub-discipline of differential equations and dynamical systems is foundational in the study of applied mathematics. Differential equationsarise in a variety of contexts, some purely theoretical and some of practic

VCU - MATH - 532

CHAPTER 2 Linear, Constant-Coefficient SystemsThere are few classes of ode s for which exact, analytical solutions can be obtained by hand. However, for many systems which cannot be solvedexplicitly, we may approximate the dynamics by using simpler sys

VCU - MATH - 532

CHAPTER 3 Nonlinear Systems: Local Theorysystems is usually impossible, so we must settle for qualitative descriptions of the dynamics. On the other hand, nonlinear systems can exhibit a wide variety of behaviors that linear systems cannot. Moreover, mos

VCU - MATH - 532

CHAPTER 4 Periodic, Heteroclinic, and Homoclinic OrbitsIn this chapter, we shift our attention away from equilibria, instead seeking more "interesting" solutions of nonlinear systems x = f (x). Much of ourdiscussion involves planar systems (i.e., f : R

VCU - MATH - 532

CHAPTER 5 BifurcationsIn practice, we often deal with ode s which contain parameters (unspecified constants) whose values can profoundly influence the dynamical behavior ofthe system. For example, suppose we model population changes for a species. The

VCU - MATH - 532

CHAPTER 6 Introduction to Delay Differential EquationsIn this Chapter, we turn our attention to delay differential equations (dde s), a major departure from the ordinary differential equations that were consideredup to now. A basic reference for this m

VCU - MATH - 532

CHAPTER 7 Introduction to Difference EquationsThis Chapter concerns the dynamical behavior of systems in which time can be treated as a discrete quantity as opposed to a continuous one. Forexample, some mathematical models of the onset of cardiac arrhy

VCU - MATH - 532

CHAPTER 8 Introduction to Partial Differential Equationsperature T depends not only upon time, but also upon spatial location. If x and y denote latitude and longitude and t denotes time, then the function T ( x, y, t) describes how temperature varies in

VCU - MATH - 532

CHAPTER 9 Linear, First-Order Partial Differential EquationsIn this chapter, we will discuss the first of several special classes of pde s that can be solve via analytical techniques. In particular, we will investigate linear,first-order pde s a( x, t)

VCU - MATH - 532

CHAPTER 10 The Heat and Wave Equations on an Unbounded DomainAt first glance, the heat equation ut - u xx = 0 and the wave equationto be positive constants, the only apparent distinction is between the ut in theutt - c2 u xx = 0 appear very similar. S

VCU - MATH - 532

CHAPTER 11 Initial-Boundary Value ProblemsThe infinite spatial domains considered in the previous chapter give insight regarding the behavior of waves and diffusions. However, since suchdomains are not physically realistic, we need to develop new techn

VCU - MATH - 532

CHAPTER 12 Introduction to Fourier SeriesIn each example, we were able to construct series representations of the solutions provided that the initial conditions themselves had special series representations (i.e., Fourier sine and cosine series). In this

VCU - MATH - 532

CHAPTER 13 The Laplace and Poisson EquationsUp to now, we have dealt almost exclusively with pde s for which one independent variable corresponds to time. Now, we will analyze a pdefor which this is not the case: Laplace's equation. To motivate where L

Lincoln U. MO - ECON - 101

05 HW7-2_solutions.gwb - Tuesday, March 10, 2009 - Page 1 of 6Captured on Tue Mar 10 2009 10:06:2905 HW7-2_solutions.gwb - Tuesday, March 10, 2009 - Page 2 of 6When you rub your sock on the carpet, your sock picks up extra electrons, which then spread

Lincoln U. MO - ECON - 101

#_NAME_PERIOD_DATE_Conservation of Momentum HW 6-21. Old cannons were built on carts with wheels. The wheels helped when moving the cannon and they would allow the cannon to recoil when fired. When a 150 kg cannon and cart recoils at 1.5 m/s, at what ve

Lincoln U. MO - ECON - 101

Periodic Table of Elements1112Atomic #34C Solid5678Metals91011Nonmetals1213141516172182 K1H3SymbolName Atomic Mass2 1HeHelium 4.002602Hydrogen 1.00794Alkali metalsAlkaline earth metalsTransition metalsPoor metalsOthe

Central Washington University - ECON - 462

MGTOP 491 Professor: Dr, Arthurs Date: Individual Case analysis: Under Armour: working to stay on top of its game Overview Under Armour, was founded by Kevin Plank, in 1996, one of the major sports clothing and accessories companies in all over the world.

Alliant - ECON - 101

Project Name: Company Name: Project Manager: Date of Report: Task Task A Task B Task C Task D Task E Task FSample Excel Gantt Chart Bright Hub Project Management Michele McDonough July 1, 2008 Start Date End Date 12/15/07 01/05/08 02/01/08 03/30/08 06/01

Colby - PSYCHOLOGY - PS215

Introduction to ANOVABring calculator on Thursday Reading in HowellRecap from last lecture Review t-testHypothesis testing Type I and II errorsIntroduction to ANOVA"Moral Blame" StudyThreat: RegressionTest-retest reliability is not perfect Error in

Stanford - STATS - 315a

ESL Chapter 7 - Model SelectionTrevor Hastie and Rob TibshiraniModel SelectionTopics Bias variance trade-off Optimism of training error Estimates of in sample prediction error BIC VC dimension Cross-validation (chapter 3), bootstrap1ESL Chapter 7 -

Stanford - STATS - 315a

ESL Chapter 5 - Basis Expansions and RegularizationTrevor Hastie and Rob TibshiraniBasis Expansions and RegularizationFor a vector X, we consider models of the formMf (X) =m=1m hm (X)Examples of hm :2 hm (X) = Xj , Xj X , . . . hm (X) = |X|, log

Stanford - STATS - 315a

ESL Chapter 4 - Linear Methods for ClassificationTrevor Hastie and Rob TibshiraniLinear Methods for Classification Linear regression linear and quadatric discriminant functions example: gene expression arrays reduced rank LDA logistic regression separa

Stanford - STATS - 315a

ESL Chapter 1 - IntroductionTrevor Hastie and Rob TibshiraniStatistical Learning Problems Identify the risk factors for prostate cancer (Fig 1.1). Classify a recorded phoneme (Fig 5.5) based on a log-periodogram. Predict whether someone will have a hea

Stanford - STATS - 315a

ESL Chapter 3 - Linear Methods for RegressionTrevor Hastie and Rob TibshiraniLinear Methods for RegressionOutline The simple linear regression model Multiple linear regression Model selection and shrinkage-the state of the art1ESL Chapter 3 - Linear

Stanford - STATS - 315a

SLDM III c Hastie & Tibshirani - March 18, 2010Dimension Reduction and SVD194Principal ComponentsSuppose we have N measurements on each of p variables Xj , j = 1, . . . , p. There are several equivalent approaches to principal components: Produce a de

Stanford - STATS - 315a

ESL Chapter 2 - Overview of Supervised LearningTrevor Hastie and Rob TibshiraniOverview of Supervised LearningNotation X: inputs, feature vector, predictors, independent variables. Generally X will be a vector of p real values. Qualitative features ar

Stanford - STATS - 315a

Notes on Statistical LearningJohn I. Marden Copyright 20062Contents1 Introduction 2 Linear models 2.1 Good predictions: Squared error loss and 2.2 Matrices and least-squares estimates . . 2.3 Mean vectors and covariance matrices . . 2.4 Prediction usi

Stanford - STATS - 315a

AgendaRegularization: Ridge Regression and the LASSOStatistics 305: Autumn Quarter 2006/2007Wednesday, November 29, 2006Statistics 305: Autumn Quarter 2006/2007Regularization: Ridge Regression and the LASSOAgendaAgenda1 2The Bias-Variance Tradeof

Stanford - STATS - 315a

Welcome to Q&A for statisticians, data analysts, data miners and data visualization experts - check out the FAQ!Stack Exchangelog in | blog | meta | about | faqStatistical Analysis Questions Tags Users Badges Unanswered Ask QuestionLeast angle regres

Stanford - STATS - 315a

Regularization and Variable Selection via the Elastic NetHui Zou and Trevor Hastie Journal of Royal Statistical Society, B, 2005 Presenter: Minhua Chen, Nov. 07, 2008 p. 1/1AgendaIntroduction to Regression Models. Motivation for Elastic Net. Naive Ela

Stanford - STATS - 315a

Linear, Ridge Regression, and Principal Component AnalysisLinear, Ridge Regression, and Principal Component AnalysisJia LiDepartment of Statistics The Pennsylvania State UniversityEmail: jiali@stat.psu.edu http:/www.stat.psu.edu/jialiJia Lihttp:/www

Stanford - STATS - 315a

Lecture 5: Multiple Linear RegressionNancy R. ZhangStatistics 203, Stanford UniversityJanuary 19, 2010Nancy R. Zhang (Statistics 203)Lecture 5January 19, 20101 / 25AgendaToday: multiple linear regression. This week: comparing nested models in mul

Stanford - STATS - 315a

Nearest Neighbor ClassificationCharles Elkan elkan@cs.ucsd.edu January 11, 2011What is called supervised learning is the most fundamental task in machine learning. In supervised learning, we have training examples and test examples. A training example i

Stanford - STATS - 315a

Locally Weighted LearningMachine Learning Dr. Barbara HammerLocally Weighted LearningInstance-based Learning ("Lazy Learning")Local Models k-Nearest Neighbor Weighted Average Locally weighted regressionCase-based reasoningWhen to consider Nearest

Stanford - STATS - 315a

Conditional Expectations and Linear RegressionsWalter Sosa-EscuderoEcon 507. Econometric Analysis. Spring 2009March 31, 2009Walter Sosa-EscuderoConditional Expectations and Linear Regressions`All models are wrong, but some are useful' (George E. P.

Berkeley - BUSINESS - 103

Short SalesAn OverviewAD.6Short SalesAn OverviewThis handout is a reproduction of section 2.4.2 (pages 25-30) of Sharpe, William F., and Gordon J. Alexander, 1990, Investments, Prentice-Hall, New Jersey.IntroductionAn old adage from Wall Street is

Berkeley - BUSINESS - 103

Frequently Asked Questions about CalculatorsCalculators are useful, but can behave in unexpected ways (at least if, like me, you don't like reading the instructions first). Here are some questions that people often have. I'm just starting this list, and

Berkeley - BUSINESS - 103

HP 12C CalculationsThis handout has examples for calculations on the HP12C: 1. Present Value (PV) 2. Present Value with cash flows and discount rate constant over time 3. Present Value with uneven cash flows but constant discount rate 4. Annuity 5. Loan

Berkeley - BUSINESS - 103

UGBA 103 Introduction to FinanceDmitry LivdanWalter A. Haas SchoolFall 2011Dmitry Livdan (Haas)UGBA 103Fall 20111 / 1790. IntroductionDmitry Livdan (Haas)UGBA 103Fall 20112 / 1790. IntroductionReadings: Berk and DeMarzo: Chapter 1.Dmitry Li

Berkeley - BUSINESS - 103

UGBA 103 Introduction to FinanceDmitry LivdanWalter A. Haas SchoolFall 2011Dmitry Livdan (Haas)UGBA 103Fall 20111 / 339I.4 The Valuation of Risky Cash FlowsDmitry Livdan (Haas)UGBA 103Fall 20112 / 339MotivationWe have by now developed a fair

Berkeley - BUSINESS - 103

UGBA 103 2010 Midterm Solutions 1. (a) 10K today: P V (11K) = (b) 1 + rnom = (1 + i)(1 + rreal ) rreal = 1.1/1.05 - 1 = 4.7619% 2. The mortgage has 17 years left, so there are N = 17 12 = 204 payments of C = 1500 remaining. The effective monthly interest

Berkeley - BUSINESS - 103

Syllabus (tentative) UGBA 103 Introduction to Finance -Fall 2011instructor: office: email: office hours: class time:ProfessorDmitry Livdan F473 livdan@haas.berkeley.edu Wednesday: 10:00 -11:30 AMUGBA103-1 MW 8:00AM-9:30AM F295 (Anderson Auditorium) UGB

Virtual University of Pakistan - BBA - 3

How to Write a Memo: Standard Conventions for Inter-Office Business Correspondence Emily Thrush March 4, 2000 MEMORANDUM TO: Mr. and Ms. Business Communicator FROM: Emily A. Thrush, Column Editor SUBJECT: Memo writing -This memo outlines how to write an e

John Wood CC - ECO - 101

Chapter 16. A Macroscopic Description of Matter Macroscopic systems are characterized as being either solid, liquid, or gas (water). These are called the phases of matter. In this chapter we'll be interested in when and how a system changes from one phas

John Wood CC - ECO - 101

Starting Monday, the Physics Learning Center (223 Kinard) will be open: M: 8:00am 9:00pm T: 8:00am 8:00pm W: 10:00am 12:00pm, 1:00pm 8:00pm TH: 8:00am 9:00pm F: 8:00am 12:00pm, 2:00pm 9:00pm There will be a homework help session on Thursday, September 1 a

John Wood CC - ECO - 101

Chapter 18. The Micro/Macro ConnectionHeating the air in a hot-air balloon increases the thermal energy of the air molecules. This causes the gas to expand, lowering its density and allowing the balloon to float in the cooler surrounding air. Chapter Goa

John Wood CC - ECO - 101

Chapter 19. Heat Engines and Refrigerators IS THERE A WAY TO TRANSFORM HEAT INTO WORK? Thermodynamics is the branch of physics that studies the transformation of energy.Copyright 2008 Pearson Education, Inc., publishing as Pearson Addison-Wesley. What

John Wood CC - ECO - 101

Chapter 26 Electric Charges and ForcesSample question:In electrophoresis, what force causes DNA fragments to migrate through the gel? How can an investigator adjust the migration rate?Copyright 2007, Pearson Education, Inc., Publishing as Pearson Addis

John Wood CC - ECO - 101

Chapter 27. The Electric FieldWhat makes the electrons flow (current) in your computer and the nerves in your body? ANS: Electric fields Electric fields also line up polymer molecules to form the images in a liquid crystal display (LCD). Chapter Goal: To

John Wood CC - ECO - 101

EG 210: CAD and Engineering Application Sections 30, 31 & 32 Fall 2011HW #1: Download AutoCAD 2010 Date Assigned: 08/25/2011 Due Date: 08/30/2011 in the beginning of the class No late submissionEx1: Download AutoCAD 2010. You can go to CCIT or download

John Wood CC - ECO - 101

EG 210: CAD and Engineering Application Sections 30, 31 & 32 Fall 2011 HW #2: Grid, Circle, Line, Copy, and Trim commands Date Assigned: 09/08/2011 Due Date: 09/15/2011 in the beginning of the classEx1: Submit the syllabus form. (The syllabus forms wer

John Wood CC - ECO - 101

EG 210: CAD and Engineering Application Sections 30, 31 & 32 Fall 2011HW #3: Linetype, Lineweight, Color, Mirror, Copy, Rotate, and Scale Date Assigned: 09/15/2011 Due Date: 09/22/2011 in the beginning of the classCreate and save the following drawings:

John Wood CC - ECO - 101

EG 210: CAD and Engineering Application Sections 30, 31 & 32 Fall 2011HW #4 Date Assigned: 09/22/2011 Due Date: 09/29/2011 in the beginning of the classCreate and save the following drawing:Ex1: Open the drawing of Ex1 of ICA #9 (the bridge drawing). (

John Wood CC - ECO - 101

EG 210: CAD and Engineering Application Sections 30, 31 & 32 Fall 2011HW #5: Pipe Cutter Figure 4, Page #462 of the textbook.(30 pt)Date Assigned: 09/29/2011 Due Date: 10/06/2011 in the beginning of the classCreate and save the following drawingEx1: