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William & Mary - PSYCH - 202
whoisthatlady?Ash?2010 CONTROL20:27I MPORTANT! * *Role of control and predictability in terms of stress and dealing w ith stress. Best established psychology fact. Notion that stress is in the eye of the holders o The same exact stress might not be str
McGill - MIME - 310
McGillFaculty of EngineeringMIME 310 Engineering EconomyChapter 4 Production and Cost Analysis Technical efficiency is an important constituent of economic efficiency. OutlineSection 1: Economics of Production Combining Technology (production function
McGill - MIME - 310
McGillFaculty of EngineeringMIME 310 Engineering EconomyChapter 5 Sources of Funds and Cost of CapitalNervus belli, pecuniam infinitum, Cicero (106-43 B.C.)The sinews of war: money in abundanceWhere does a business obtain funds to finance its projec
McGill - MIME - 310
McGillFaculty of EngineeringMIME 310 Engineering EconomyChapter 6 Project Evaluation CriteriaHow do you make a million? You start with $900 000., Stephen LewisSection 1: Introduction Cash Flow A formal definitionSection 2: Investment Criteria How do
McGill - MIME - 310
MIME 310 ENGINEERING ECONOMYPROBLEM EXERCISESFALL 2009Department of Mining, Metals and Materials EngineeringMcGill UniversityFOREWORD There are ten sets of problem exercises, one for each chapter in the notes. Their purpose is to help you practice so
McGill - MIME - 310
MIME 310ENGINEERINGECONOMYSOLUTIONS TO PROBLEM SET #4 PRODUCTION AND COST ANALYSES 1. The recovery method with the highest unit profit (revenue less cost) is preferred. Process B has a higher recovery than process A, but it also has a higher cost. Thus
McGill - MIME - 310
MIME 310ENGINEERINGECONOMYSOLUTIONS TO PROBLEM SET #5 SOURCES OF FUNDS AND THE COST OF CAPITAL1. The company's current cost of capital, as opposed to that associated with issuing additional funds, is determined by omitting the issuing expenses that wo
McGill - MIME - 310
MIME 310ENGINEERINGECONOMYSOLUTIONS TO PROBLEM SET #6 PROJECT EVALUATION CRITERIA 1. The present worth cost equivalent (PW) of each machine is determined at a discount rate of 10 percent. Under the repeated-projects assumption, the machines must be com
McGill - MIME - 310
MIME 310 ENGINEERING ECONOMYTUTORIAL PROBLEMSFALL 2009Department of Mining and Materials EngineeringMcGill UniversityFOREWORD This document contains a series of short problems that will be solved during the tutorial periods. Their purpose is to give
McGill - MIME - 310
McGillFaculty of EngineeringMIME 310 Engineering EconomyTutorialsChapter 4. Production and Cost Analyses1McGillFaculty of EngineeringMIME 310 Engineering Economy4.1 Consider the following total revenue (TR) and cost (TC) functions: TR = 350 Q - 0
McGill - MIME - 310
McGillFaculty of EngineeringMIME 310 Engineering EconomyTutorialsChapter 5. Sources of Funds and Cost of Capital1McGillFaculty of EngineeringMIME 310 Engineering Economy5.1 Mr Brown, one of the directors of a sewage company, urges that more debt
McGill - MIME - 310
McGillFaculty of EngineeringMIME 310 Engineering EconomyTutorialsChapter 6. Project Evaluation Techniques1McGillFaculty of EngineeringMIME 310 Engineering EconomyTutorials6.1 Given the following items from the financial records of a company, det
Keller Graduate School of Management - MISM - TM583
Case4 Google: Research Googles attempt to buy into wireless via the 700 MHz Spectrum Auction Course: TM583 1. Why did Google making this move? What do they hope to accomplish? Everyone from mobile operators to public-safety companies to Google sees the sp
Cornell - S&TS - 2011
STS 2011/SOC 2100 March 31, 20101Epistemic authority versus moral authority Steve Shapin: On what groundsdo we trust scientists to tell the truth about the natural world? T Trust is central to knowledge in general, and also central to scientific knowled
Cornell - S&TS - 2011
STS 2011/SOC 2100April 12, 20101 The laboratory matters, as a specific site ofscientific knowledge-making What material and social orderings andarrangements are manifested in the design,construction, and operation of laboratories? How do these ord
Cornell - S&TS - 2011
S&TS 2011, SOC 2100: What is Science? Four Credit Special Section Application The special section for What is Science? will provide interested students with the opportunity to engage with course material in a deeper and more active way. The section will b
Cornell - S&TS - 2011
Scientific and Other Expertise in Risk Governance(illustrated with the case of nanotechnologies in the Netherlands)Wiebe E. BijkerMaastricht UniversityCornell University STS 2011/SOC 2100 7th April 2010We live in a Technological CultureWe cannot hop
Cornell - S&TS - 2011
Boundary-work1What makes science special? Two sets of perspectives Popperian concept of falsifiability Mertonian norms Claim: these demarcations are uniqueamong other knowledge-making practices and account for sciences epistemic authority2Challeng
Cornell - S&TS - 2011
Criteria for Peer Review Instructions 1) Read your assigned draft paper. 2) After you read the paper once, describe 3 strengths + 3 weaknesses of the paper you are reviewing based on the following 5 sets of criteria. You do not have to answer all of the q
Cornell - S&TS - 2011
February 8, 2010 STS 2011/SOC 21001Systems of organization, control, purity that are set apart from the natural world More than just observation, rather intervention Takes an enormous amount of work, resources, skill2Does it match with theory/other ex
Cornell - S&TS - 2011
STS 2011/SOC 2100: What is Science? An Introduction to Science and Technology Studies Professor Kathleen Vogel January 25, 20101WELCOME! Getting to know you.me.TAs Lets talk about science and technology! Course business2Getting to know you3Getting t
Cornell - S&TS - 2011
January 27, 2010 STS 2011/SOC 21001Physics of the Universe SummitDennis Overbye, Physicists Dreams and Worries inEra of the Big Collider, The New York Times, January 26, 2010 Notable physicist gathering at the Riot Hyatt in Los Angeles for weekend dis
Cornell - S&TS - 2011
STS 2011/SOC 2100, What is Science? Midterm Essay Assignment 4-credit Writing Section Assignment: Select a scientific controversy from contemporary science (or technology) or the history of science. The controversy can be within a particular science or ca
Cornell - S&TS - 2011
1Mid-term Study Guide Identification: Using complete sentences, briefly identify (X number) of the following items and state its significance in the context of the course. Write only two to four sentences. IDs listed on mid-term exam will come directly f
Cornell - S&TS - 2011
PEDAGOGY AND LAB PRACTICESTS 2011/SOC 2100 March 10, 20101Pedagogy: Teaching/training E Classroom instructionEBroader institutions and practices by which novices become working scientists and engineers2Training is not neutral or passive; future of
Cornell - S&TS - 2011
STS 2011/SOC 2100 February 15, 20101Discovery is central to common conceptions of science Largely focused on an event, person, and self-evident findingsTStakes are high: rewards for priority Involves novelty and significance How are these determined?
Cornell - S&TS - 2011
Scientific Method(s)1 Observations Formulation of hypotheses Predictions from hypotheses Testing the hypotheses through experiment2Vienna Circle (~1920-1930s): development of new philosophical understandings of science Scientific theories are evaluat
Cornell - S&TS - 2011
1What was the social context that shaped the discovery of the AIDS virus? h Who/what counted in the discovery? What was left out? How did this occur? h What impressions do you have of Gallo and his scientific conduct?hHow does this account affect how y
Cornell - S&TS - 2011
Scientific Representations1British zoologist & immunologist Royal society member at 34 Work on graft rejection and the discovery of acquired immune tolerance Won the Nobel Prize in Physiology or Medicine in 1960Peter Medawar2Wrote controversial paper
Cornell - S&TS - 2011
1Horace Walpole 1754, The Three Princes of Serendip Serendipity is the "making discoveries by accident and sagacity, of things which one is not on quest of. Joseph Priestly, 1775 more is owing to what we call chance, that is, philosophically speaking, to
Cornell - S&TS - 2011
Special Writing Section Guidelines Reading Responses Students are given the opportunity to more fully explore their engagement with the readings and flexibility is given in the reading responses. The responses are due in section in hard copy and you shoul
Cornell - S&TS - 2011
1 STS 2011/SOC 2100: WHAT IS SCIENCE? AN INTRODUCTION TO SCIENCE AND TECHNOLOGY STUDIES Course Instructor: Professor Kathleen Vogel Department of Science and Technology Studies 330 Rockefeller Hall email: kmv8@cornell.edu; 607-255-2248 10:10-11:00 a.m. MW
Cornell - S&TS - 2011
12In-class exercise: Learning How to snowboard?nWhat are the rules for snowboarding?3Polanyi and Tacit KnowledgenMichael Polanyi: physical chemist, early 1950s First to articulate in scientific lectures the concept of tacit knowledge skilled scien
Cornell - S&TS - 2011
1The Making of ExpertiseSTS 2011/SOC 2100 April 5, 2010Credibility and Scientific Expertise Who is an expert on scientific and technological issues? How is expertise constituted, maintained, contested, negotiated, and defended? What are the implicatio
Cornell - S&TS - 2011
STS 2011/SOC 2100 February 1, 20101The Special Character of Science Science as pure and objective Interrogating this claim Is it true? How so? More generally speaking: What is it about science that makes it a morereliable knowledge producing system
Cornell - S&TS - 2011
STS 2011/SOC 2100 February 3, 20101Neutrality of observation Facts/claims about natural world are directly observableTTheory laden observation Scientific observation is a developed skill2Neutrality of Observation: Facts are prior to and independent
Cornell - S&TS - 2011
S&TS 2011, SOC 2100: What is Science? Four Credit Special Section Application The special section for What is Science? will provide interested students with the opportunity to engage with course material in a deeper and more active way. The section will b
Cornell - STSCI - 3200
Biological Statistics IIBiometry 3020 / Natural Resources 4130 / Stat Sci 3200Homework 1 Due on Thursday February 4 The questions below are from Kutner, Nachtsheim, Neter and Li Applied Linear Statistical Models, but some of these questions could be loo
Cornell - STSCI - 3200
Biological Statistics II Biometry 3020 / Natural Resources 4130 / Stat Sci 3200 Homework 1 Due on Thursday February 4 The questions below are from Kutner, Nachtsheim, Neter and Li Applied Linear Statistical Models, but some of these questions could be loo
Cornell - STSCI - 3200
Biological Statistics II Biometry 3020 / Natural Resources 4130 / Stat Sci 3200 Homework 2 Due on Thursday February 11 1. Now that you are familiar with the grade point average data consider the diagnostics problem KNNL 3.3, do all components of this prob
Cornell - STSCI - 3200
Biological Statistics II Biometry 3020 / Natural Resources 4130 / Stat Sci 3200 Homework 2 Due on Thursday February 11 1. Now that you are familiar with the grade point average data consider the diagnostics problem KNNL 3.3, do all components of this prob
Cornell - STSCI - 3200
Name: Section:Biological Statistics II Biometry 3020 / Natural Resources 4130 / Statistical Science 3200Homework 3 Due on Thursday February 18 1. (4 points) KNNL 6.23 a. Consider the multiple regression model Yi = 1 X i1 + 2 X i 2 + i i = 1,., n2 2 whe
Cornell - STSCI - 3200
Biological Statistics II Biometry 3020 / Natural Resources 4130 / Statistical Science 3200 Homework 4 Worth 20 points SENIC Data The primary objective of the Study on the Efficacy of Nosocomial Infection Control (SENIC Project) was to determine whether in
Cornell - STSCI - 3200
Biological Statistics II Biometry 3020 / Natural Resources 4130 / Statistical Science 3200 Homework 5 Worth 20 points Due Thursday March 18, 2010Fat in diets. (Problem 21.7) A researcher studied the effects of three experimental diets with varying fat co
Cornell - STSCI - 3200
Biological Statistics I Biometry 3020 / Natural Resources 4130 / Statistical Science 3200 Lab 1 Name: Section: Date: This lab is meant to facilitate understanding the difference between estimating the mean of Y for a particular X and a new Y for a particu
Cornell - STSCI - 3200
Biological Statistics II Biometry 3020 / Natural Resources 4130 / Statistical Science 3200 Lab 2 Name: Section: Date: Today we shall develop a matrix approach to simple linear regression analysis implementing what we covered in Lec05.Matrix2.ppt. Flavor d
Cornell - STSCI - 3200
BiologicalStatisticsIIBRTY3020/NTRES4130/STSCI3200Spring4credits Lecture:TueandThu10:1011:25 RileyRobb105 Lab: Tuesday12:201:10,MannLibraryB30B Tuesday1:252:15,MannLibraryB30B 214Fernow 2558213 Instructor: Dr.PatrickJ.Sullivanpjs31@cornell.eduTeachin
Cornell - STSCI - 3200
Regression Parameter EstimationKNNL Ch. 1, Ch. 2Overview of Todays Lecture Probability Density,cumulative distribution Expected Means,Valuesvariances Leastsquares Parameter estimation, the linear model Maximum likelihood Example: Ping-pongBino
Cornell - STSCI - 3200
Regression DiagnosticsKNNL Ch. 3 Lec03.Diagnostics Exercises.ppt Lec03.Diagnotics.sscRecap Last Lecture Expected valueTheoretical mean from probability distributionObjective: Minimize sum of squares Derivative with respect to parameters Relationship
Cornell - STSCI - 3200
Matrix AlgebraKNNL Ch. 5Why use matrix formulations?It will give us a more compact and efficient method of describing and remembering statistical relationships such as those used in linear regression. It will provide a shorthand notation for carrying o
Cornell - STSCI - 3200
Matrix Algebra and RegressionKNNL Ch. 5X Matrix1 X 1 1 X 2 X = 1 X n 1 1 X n attach(sparrow) Xmat=cbind( rep(1,length(age.days), age.days) Xmat integermatrix:13rows,2 columns. [,1][,2] [1,]13 [2,]14 [3,]15 [4,]16 [5,]18 [6,]19.Product of X Matrix1 X
Cornell - STSCI - 3200
RegressionThroughthe OriginKNNLCh.4,Section4.4 P161165Whenappropriate?Theoryorempiricalevidencethat:Ecfw_Y isproportionaltoX. Interceptnotsignificantlydifferentfrom zero(pvalue>0.05). Equalvariance,normalityand independenceassumptions:satisfied.Regres
Cornell - STSCI - 3200
Bootstrap ResamplingAppliedtoNormalandNonnormal RegressionData KNNL11.5Leaf Length30 0 20 10 204060 leaves80100The Mean (Average Leaf Length) Population1 = Xi N i =1nNSample1 x = xi n i =1Measures of Variation for Two Different, but Related,
Cornell - STSCI - 3200
Biological Statistics II Review 1Whathavewelearnedthusfar? Whattoolsdowenowhaveavailable?What are we attempting to do?Findarelationshipbetweenapredictor andaresponsevariable? Characterizetherelationship parsimoniously Beabletopredictmeanandstandard err
Cornell - STSCI - 3200
Polynomial RegressionKutner, Nachtsheim, Neter and Li Chapter 8.1Polynomial RegressionMultiple Linear Regressionyi = 0 + 1 x1i + 2 x2i + 3 x3i + 4 x4i + iPolynomial Regression2 2i 3 3i 4 4iyi = 0 + 1 xi + x + x + x + iAlligator Weight vs. Lengtha
Cornell - STSCI - 3200
Multiple RegressionKNNL Chapter 6 6.1 Intro 6.2 Matrix 6.5 ANOVA 6.6 Parameters 6.7 Mean Response 6.8 Diagnostics 6.9 ExampleMultiple Predictors Single Responseyi = 0 + 1 x1i + 2 x2i + 3 x3i + 4 x4i + i yi = 0 + k xki + ik =1 p 1Y = X + Coal-Ash Dat
Cornell - STSCI - 3200
Model SelectionKNNLChapter9(9.19.3) BuildingtheRegressionModelIChoosing the Best ModelBestFitting(SmallestSumofSquares) MostParsimonious(FewestParameters) BestPredictor MostHelpful(PredictiveSense) EasiesttoInterpret EasiesttoModifyandUpdate Cheapest N
Cornell - STSCI - 3200
MultipleRegression DiagnosticsKNNLChapter10(10.110.3,10.5) BuildingtheRegressionModelII ClicktoeditMastersubtitlestyle Lec12.MultiDiag.sscMakesuretoreadMulticolinearity:KNNLChapters7.6,10.5CommentssectionalsoAddingordeletingapredictorvariablechanges
Cornell - STSCI - 3200
Multiple Regression Diagnostics and Remedial MeasuresKNNL Chapter 10.1,10.5Overview of todays lecture Checkingfor information contained in additional variables Identifying the symptoms of colinearity Weighted least squaresModel Adequacy Areadded va
Cornell - STSCI - 3200
I ntr oduction to D esign of Exper imentsKNNL Ch. 15D esign T er minology Factor is an explanatory variable in the experiment (independent variable) Factor levels are the forms of the factor used in the experiment A treatment is a combination of factor
Cornell - STSCI - 3200
Analysis of Variance (ANOVA) One-way ANOVA, KNNL Chp. 16 Two-way ANOVA, KNNL Chp. 19Poplar Trees Marathon TimesSingle-Factor (One-way) ANOVATreatment Weight (kg) Poplar Trees None 0.15 0.02 0.16 0.37 0.22 5 0.184 0.127 Fertilizer 1.34 0.14 0.02 0.08 0.