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- Title: SCA_examples
- Type: Notes
- School: Maryland
- Course: EDCI 788
- Term: Fall
Coursehero >> Maryland >> Maryland >> EDCI 788
Path: Maryland >> CTP >> 1 Fall, 2008
Path: Maryland >> GLUE >> 776 Fall, 2008
Path: Maryland >> BB >> 8 Fall, 2008
Path: Maryland >> BB >> 8 Fall, 2008
Path: Maryland >> ECE >> 2006 Fall, 2008
Path: Maryland >> ECE >> 2006 Fall, 2008
Path: Maryland >> ECE >> 2006 Fall, 2008
Path: Maryland >> ECE >> 2006 Fall, 2008
Path: Maryland >> ECE >> 2006 Fall, 2008
Path: Maryland >> ECE >> 2006 Fall, 2008
Path: Maryland >> ECE >> 2006 Fall, 2008
Path: Maryland >> ECE >> 2006 Fall, 2008
Path: Maryland >> CSCAMM >> 08 Fall, 2008
Path: Maryland >> ECON >> 454 Fall, 2008
Path: Maryland >> ECON >> 454 Fall, 2008
Path: Maryland >> ECON >> 454 Fall, 2008
Path: Maryland >> ECON >> 454 Fall, 2008
Path: Maryland >> ECON >> 454 Fall, 2008
Path: Maryland >> ECON >> 454 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 454 Fall, 2008
Path: Maryland >> ECON >> 454 Fall, 2008
Path: Maryland >> ECON >> 454 Fall, 2008
Path: Maryland >> ECON >> 454 Fall, 2008
Path: Maryland >> ECON >> 454 Fall, 2008
Path: Maryland >> ECON >> 454 Fall, 2008
Path: Maryland >> ECON >> 454 Fall, 2008
Path: Maryland >> ECON >> 454 Fall, 2008
Path: Maryland >> ECON >> 454 Fall, 2008
Path: Maryland >> ECON >> 454 Fall, 2008
Path: Maryland >> ECON >> 454 Fall, 2008
Path: Maryland >> ECON >> 454 Fall, 2008
Path: Maryland >> ECON >> 454 Fall, 2008
Path: Maryland >> ECON >> 454 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
Path: Maryland >> ECON >> 422 Fall, 2008
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Framework Structure/Culture/Agency Formal rules Formal policies Formal procedures Arrangements of people Arrangements of resources Arrangements of objects and space STRUCTURE CULTURE Social climate Normative beliefs Normative practices Interpersonal relations Inter-group relations AGENCY Individuals actions Individuals behaviors Individuals beliefs Individuals perceptions Structure Formal rules, policies and procedures Expectations and guidelines that are written down. In school, they can be found in things like the student handbook and the code of conduct or posted on the walls of classrooms. Examples: No wearing hats is a rule in many schools. School policy might state that a student caught wearing a hat will get one day of detention. The procedure the way things are officially done may be to have the student stay after school for one hour and to call the student s parent. Arrangements of people Peoples positions in relation to other people. Usually, one person or group is in a better or more powerful position than another. Examples: You are a student and Mr. Benn is an administrator. Some people are rich and other people are poor. Some students are in high-level classes and others are in lowlevel classes. Arrangements of resources Who has resources and who does not. Resources are things that can make your life better. They include things like money, education, health care and information. Examples: In general, white kids go to better schools than Black and Latino kids. Rich people have better health care than poor people. In general, middle-class parents know how the school system works better than working-class parents. Arrangements of objects and space Where things are located and how they are set up. Examples: Your school is located in a commercial building. The teacher s desk is in the front of the room and the students desk face the teacher. In inner cities, people s home are usually very close together. Culture Social climate The atmosphere or overall feeling of a place. The place could be a neighborhood, a school or even a whole city. Examples: The neighborhood I grew up was in friendly and almost everyone knew each other. I once worked in a school that was very tense because a lot of students had beef with other students. Right after 9/11, there was a lot of fear in large cities. Normative beliefs Beliefs that a lot of people share. This does not mean that they are always true. * Normative means normal or typical and widespread. Examples: Students should obey their teachers. Blacks do not care about education as much as whites. If you try, you will succeed. Normative practices Typical or widespread ways of doing things. Examples: Children line up single-file to leave the classroom. Students raise their hand before speaking in class. People say, Bless you, when someone sneezes. How one person interacts with and thinks about another person. Examples: Two students get into a fight. You and your mom get along really well. A clerk follows you in a store because you re black. Inter-group relations How one group of people interacts with and thinks about another group of people. Examples: Latinos and Blacks work together against police brutality. Teachers in a school are afraid of the students. Bloods and Crips declare a truce. Interpersonal relations Agency Individuals actions What a person does. Examples: You turn in your homework assignment. I don t call my friend because I m mad at him. A student text-messages on his phone in class because he s bored. What a person does but it s usually a pattern something the person does over and over again. Examples: A teacher praises students when they do well. A child usually does what their mom tells them to do. A police officer harasses kids that hang out in the park. Individuals beliefs and perceptions What a person believes or thinks is going on. People form beliefs and perceptions based on what they see, hear and experiences. Examples: A girl thinks she is a talented singer. I believe that all students want to do well in school. A person believes that we live in a racist country. Someone believes that human beings are basically good. A teacher thinks that a student doesn t care about school. Individuals behaviors
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Path: Maryland >> EDCI >> 788 Fall, 2008
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spacetimeprimer.psPath: Maryland >> GLUE >> 776 Fall, 2008
Description: A SPACETIME PRIMER T. A. Jacobson July 30, 1998 Contents 1 Spacetime 1.1 1.2 1.3 1.4 Di erential structure Spacetime diagrams : Causal structure : : : Metrical structure : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : ...
managing_content_collection_v8.pdfPath: Maryland >> BB >> 8 Fall, 2008
Description: ELMS: Managing the Content Collection in Blackboard Academic Suite (version 8.0) Institute for Instructional Technology Office of Information Technology Version 3.0 Copyright Office of Information Technology, University of Maryland 1 Table of C...
setup_Wiki_page_in_Bb.docPath: Maryland >> BB >> 8 Fall, 2008
Description: Setup Wiki Pages in Blackboard Wiki Tool in Blackboard is a page or collection of Web pages that allows users to contribute or modify content, upload images, documents, and users may export the wiki pages into a zip file. Here is some instructions of...
Poster_1_Chang.pdfPath: Maryland >> ECE >> 2006 Fall, 2008
Description: Electron Beam Induced Deposition of Platinum Contacts Daniel Chang, Matthew Ervin, John Barry, Barbara Nichols, John Melngailis, Alma Wickenden Nanoscale Material Integration The integration of non-conventional materials such as polymer fibers into ...
Poster_2_Dorsey.pdfPath: Maryland >> ECE >> 2006 Fall, 2008
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Description: Integration of Functional Nano-Technology Materials on a Single Chip Ratanak Heng, Dr. Stephen Kilpatrick, Dr. Alma Wickenden, Dr. RD Vispute, Dr. Shiva Hullavarad, Dr. T. Venkatesan Minimizing Size, Maximizing Functionality Thin Film Structures Z...
Poster_4_Rusak.pdfPath: Maryland >> ECE >> 2006 Fall, 2008
Description: Introduction and Overview Motivation and Objective The purpose of this project is to study novel carbon nanotube-embedded chemical sensors that can detect environmentally toxic microscopic agents. Carbon nanotubes (CNTs) are rolled sheets of carbon...
Poster_7_Webb.pdfPath: Maryland >> ECE >> 2006 Fall, 2008
Description: Detection of Humans Carrying Concealed Objects Jeremy Webb, Yang Ran, and Dr. Rama Chellappa Problem: Detect concealed objects on the ankle and around the midsection by looking at gait changes using computer vision techniques Detect deviations to the...
Poster_9_Ogunsuyi.pdfPath: Maryland >> ECE >> 2006 Fall, 2008
Description: SPEAKER RECOGNITION AND VOICE MINING Olakunle Ogunsuyi, Dr. Carol Y. Espy-Wilson, Sandeep Manocha and Srikanth Vishnubhotla INTRODUCTION This work investigated issues related to speaker recognition, with emphasis on speech detection in multi-speaker...
Poster_10_Raja.pdfPath: Maryland >> ECE >> 2006 Fall, 2008
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Poster_11_Ropp.pdfPath: Maryland >> ECE >> 2006 Fall, 2008
Description: Nonlinear MZI as a DPSK Regenerator Chad Ropp and Dr. Julius Goldhar Transmitter Receiver Introduction Fiber optic technology is fundamental for modern high speed long distance communication. Up until now commercial communication systems utilized si...
CLK08-Li.pdfPath: Maryland >> CSCAMM >> 08 Fall, 2008
Description: A Dielectric Invisibility Carpet Jensen Li Prof. Xiang Zhangs Research Group Nanoscale Science and Engineering Center (NSEC) University of California at Berkeley, USA Theory developed with Sir John Pendry, Imperial College London, UK CLK08 - 09/22/2...
Problem Set 1.pdfPath: Maryland >> ECON >> 454 Fall, 2008
Description: ECON 454, Fall 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #1 Question 1 Why does redistribution cause e ciency losses? Why might society choose to redistribute resources from one group to another when doing so...
Problem Set 2.pdfPath: Maryland >> ECON >> 454 Fall, 2008
Description: ECON 454, Fall 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #2 Question 1 Andrew, Beth and Cathy live in Lindhville. Andrew demand for bike paths, a public good, is given by s Q = 12 2P . Beth demand is Q = 18 P...
Problem Set 3.pdfPath: Maryland >> ECON >> 454 Fall, 2008
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Problem Set 4.pdfPath: Maryland >> ECON >> 454 Fall, 2008
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Problem Set 5.pdfPath: Maryland >> ECON >> 454 Fall, 2008
Description: ECON 454, Fall 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #5 Question 1 Suppose a nation has a tax rate of 10% on the rst $20,000 of taxable income, then 25% on the next $30,000, then 50% on all taxable income...
Problem Set 6.pdfPath: Maryland >> ECON >> 454 Fall, 2008
Description: ECON 454, Fall 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #6 Question 1 For which group of workers is the substitution eect associated with a tax increase more likely to outweigh the income eect: primary earne...
Empirical Project.pdfPath: Maryland >> ECON >> 422 Fall, 2008
Description: ECON 422, Spring 2007 Department of Economics, University of Maryland Jessica Hennessey Empirical Research Paper The due date for this assignment is May 10th. This project counts for 15% of your course grade. Point of the Empirical Paper I have ass...
Problem Set 1.pdfPath: Maryland >> ECON >> 422 Fall, 2008
Description: Econ 422, Spring 2007 Problem Set #1 Question 1 Prove that V (a + bX) = b2 V (X), where X is a random variable. Question 2 Show that if X and Y are independent random variables, then cov(X; Y ) = 0 Question 3 If fx1 ; x2 ; :x25 g is a random sample...
Problem Set 2.pdfPath: Maryland >> ECON >> 422 Fall, 2008
Description: ECON 422, Spring 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #2 Question 1 Let kids denote the number of children ever born to a woman, and let educ denote years of education for the woman. A simple model relat...
Problem Set 3.pdfPath: Maryland >> ECON >> 422 Fall, 2008
Description: ECON 422, Spring 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #3 Question 1 Suppose the following equation is estimated using data on 4,137 college students colgpa colgpa hsperc sat = = = = 1:392 0:0135hsperc + ...
Problem Set 4.pdfPath: Maryland >> ECON >> 422 Fall, 2008
Description: ECON 422, Spring 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #4 Question 1 Which of the following can cause the usual OLS t-statistics to be invalid (that is, not to have t-distributions under Ho )? (i) Heteros...
Problem Set 5.pdfPath: Maryland >> ECON >> 422 Fall, 2008
Description: ECON 422, Spring 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #5 Question 1 The following equation was estimated, where sleep is the total minutes per week spent sleeping at night, totwrk is total weekly minutes...
Quiz 1.pdfPath: Maryland >> ECON >> 422 Fall, 2008
Description: ECON 422, Spring 2007 Department of Economics, University of Maryland Jessica Hennessey Quiz #1 (30) Question 1 Let Y1 ; Y2 ; Y3 be independent, identically distributed random variables from a population with mean variance 2 . Let Y = 1 (Y1 + Y2 + Y...
Quiz 2.pdfPath: Maryland >> ECON >> 422 Fall, 2008
Description: ECON 422, Spring 2007 Department of Economics, University of Maryland Jessica Hennessey Quiz #2 (20) Question 1 (10) (10) 1. Write the expression for the variance of c . 1 2. How in practice would you estimate the variance of c when you can directl...
Quiz 3.pdfPath: Maryland >> ECON >> 422 Fall, 2008
Description: ECON 422, Spring 2007 Department of Economics, University of Maryland Jessica Hennessey Quiz #3 (20) Question 1 For each of the following points, determine whether or not they will cause the usual OLS t-statistics to be invalid. Explain why you came...
Quiz 4.pdfPath: Maryland >> ECON >> 422 Fall, 2008
Description: ECON 422, Spring 2007 Department of Economics, University of Maryland Jessica Hennessey Quiz #4 (25) Question 1 Suppose that you wished to estimate the eect of education on earnings (ie the returns to education) using data for a cross-section of wor...
Computer Problem Set 1.pdfPath: Maryland >> ECON >> 422 Fall, 2008
Description: ECON 422, Spring 2007 Department of Economics, University of Maryland Jessica Hennessey Computer Problem Set #1: Getting familiar with STATA The due date for this assignment is March 8th. Instructions. STATA commands are included within the descripti...
Computer Problem Set 2.pdfPath: Maryland >> ECON >> 422 Fall, 2008
Description: ECON 422, Spring 2007 Department of Economics, University of Maryland Jessica Hennessey Computer Problem Set #2: Hypothesis Testing and Comparison of Models The due date for this assignment is April 24th. Instructions. STATA commands are included wit...
PS2.txtPath: Maryland >> ECON >> 422 Fall, 2008
Description: -log: C:\\Documents and Settings\\Jessica Hennessey\\My Documents\\Jess\\Teach\\422 Spring 07\\Computer\\PS2.txt log type: text opened on: 8 Apr 2007, 14:14:25 . set mem 100m (102400k) . set matsize 800 . set more off . use \"data\\malaria\" . describe Contains...
Midterm.pdfPath: Maryland >> ECON >> 422 Fall, 2008
Description: ECON 422, Spring 2007 Department of Economics, University of Maryland Jessica Hennessey Midterm Exam (8) Question 1: Variance (6) (a) Prove that V (a + bX) = b2 V (X), where X is a random variable. (2) (b) Explain in words why a does not factor into...
Problem Set 1.pdfPath: Maryland >> ECON >> 454 Fall, 2008
Description: ECON 454, Summer 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #1 Question 1 Why does redistribution cause e ciency losses? Why might society choose to redistribute resources from one group to another when doing ...
Problem Set 2.pdfPath: Maryland >> ECON >> 454 Fall, 2008
Description: ECON 454, Summer 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #2 Question 1 Can an activity generate both positive and negative externalities at the same time? Explain your answer. Question 2 Suppose that deman...
Problem Set 3.pdfPath: Maryland >> ECON >> 454 Fall, 2008
Description: ECON 454, Summer 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #3 Question 1 Seven in ten students attending publicly funded universities leave the state after graduation, indicating that a very larger fraction o...
Problem Set 4.pdfPath: Maryland >> ECON >> 454 Fall, 2008
Description: ECON 454, Summer 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #4 Question 1 In his research, the author of your textbook found evidence that the elasticity of labor supply with respect to disability insurance be...
Problem Set 5.pdfPath: Maryland >> ECON >> 454 Fall, 2008
Description: ECON 454, Summer 2007 Department of Economics, University of Maryland Jessica Hennessey Problem Set #5 Question 1 Suppose a nation has a tax rate of 10% on the rst $20,000 of taxable income, then 25% on the next $30,000, then 50% on all taxable inco...
Midterm.pdfPath: Maryland >> ECON >> 454 Fall, 2008
Description: ECON 454, Summer 2007 Department of Economics, University of Maryland Jessica Hennessey Midterm Exam (10) Question 1 Does taxing the wealthy to give benets to the poor increase social welfare? Explain. (20) Question 2 Suppose that the demand for a...
Final.pdfPath: Maryland >> ECON >> 454 Fall, 2008
Description: ECON 454, Summer 2007 Department of Economics, University of Maryland Jessica Hennessey Final Exam (20) Question 1: Tax Incidence Let say that College Park decided that it would impose a tax on every cup of coee that Starbucks sold. s Assume that th...
Problem Set 1.pdfPath: Maryland >> ECON >> 454 Fall, 2008
Description: ECON 454, Spring 2009 Department of Economics, University of Maryland Jessica Hennessey Problem Set #1 Question 1 Why does redistribution cause e ciency losses? Why might society choose to redistribute resources from one group to another when doing ...
Problem Set 1.pdfPath: Maryland >> ECON >> 454 Fall, 2008
Description: ECON 454, Fall 2008 Department of Economics, University of Maryland Jessica Hennessey Problem Set #1 Question 1 Why does redistribution cause e ciency losses? Why might society choose to redistribute resources from one group to another when doing so...
Problem Set 2.pdfPath: Maryland >> ECON >> 454 Fall, 2008
Description: ECON 454, Fall 2008 Department of Economics, University of Maryland Jessica Hennessey Problem Set #2 Question 1 Your utility function is U = ln(2C) where C is the amount of consumption you have in any given period. Your income is $40,000 per year an...
Problem Set 3.pdfPath: Maryland >> ECON >> 454 Fall, 2008
Description: ECON 454, Fall 2008 Department of Economics, University of Maryland Jessica Hennessey Problem Set #3 Question 1 Matt is an employee at a large university, where he pays $120 a month in insurance premiums and his employer pays $300 per month. He nds ...
Problem Set 4.pdfPath: Maryland >> ECON >> 454 Fall, 2008
Description: ECON 454, Fall 2008 Department of Economics, University of Maryland Jessica Hennessey Problem Set #4 Question 1 Suppose a nation has a tax rate of 10% on the rst $20,000 of taxable income, then 25% on the next $30,000, then 50% on all taxable income...
Problem Set 5.pdfPath: Maryland >> ECON >> 454 Fall, 2008
Description: ECON 454, Fall 2008 Department of Economics, University of Maryland Jessica Hennessey Problem Set #5 Question 1 Andrew, Beth and Cathy live in Lindhville. Andrew demand for bike paths, a public good, is given by s Q = 12 2P . Beth demand is Q = 18 P...
Lecture 1.pptPath: Maryland >> ECON >> 454 Fall, 2008
Description: Lecture 1 Introduction to Public Finance Why study Public Finance? Understand the role of the government in the economy Three Perspectives Understand why and when governments get involved Understand why and what services are provided Unders...
Lecture 1.pdfPath: Maryland >> ECON >> 422 Fall, 2008
Description: Lecture 1 Introduction to Econometrics What is Econometrics? From Tintner, A Definition of Econometrics, Econometrica (1953) An econometrician is An economist, who needs to utilize correct economic theory A mathematician, who needs to use appropria...
Lecture 2.pdfPath: Maryland >> ECON >> 422 Fall, 2008
Description: Lecture 2 Review of Probability and Statistics Random Variables Probability Distributions Discrete Variable Continuous Variable x Important distinction of mean: population versus sample What is a mean? Population mean: weighted average of poss...
Lecture 3.pdfPath: Maryland >> ECON >> 422 Fall, 2008
Description: Lecture 3 February 1, 2007 Review of Probability and Statistics Quick review of last class Sample versus Population Random variables and sampling distribution Known parameters (,2) Unbiased estimator E ( ) = Consistency Definition: An estimator...
Lecture 3.pptPath: Maryland >> ECON >> 422 Fall, 2008
Description: Lecture 3 February 1, 2007 Review of Probability and Statistics Quick review of last class Sample versus Population Random variables and sampling distribution Known parameters (,2) Unbiased estimator E ( ) = Consistency Definition: ...
Lecture 4.pdfPath: Maryland >> ECON >> 422 Fall, 2008
Description: Lecture 4 February 6, 2007 Review of Probability and Statistics Quick review of last class Consistency Normal Distribution Any linear combination of normally distributed variables yields a normally distributed variable Confidence Interval It is a r...
Lecture 4.pptPath: Maryland >> ECON >> 422 Fall, 2008
Description: Lecture 4 February 6, 2007 Review of Probability and Statistics Quick review of last class Consistency Normal Distribution Any linear combination of normally distributed variables yields a normally distributed variable It is a random interval [...
Lecture 5.pdfPath: Maryland >> ECON >> 422 Fall, 2008
Description: Lecture 5 February 8, 2007 Review of Probability and Statistics 2 random variables: Joint Distribution Joint probability density function Marginal probability density function Independence Why important? Definition of independence: Useful conclus...
Lecture 5.pptPath: Maryland >> ECON >> 422 Fall, 2008
Description: Lecture 5 February 8, 2007 Review of Probability and Statistics 2 random variables: Joint Distribution Joint probability density function Marginal probability density function Independence Why important? Definition of independence: Useful...
Lecture 6.pdfPath: Maryland >> ECON >> 422 Fall, 2008
Description: Lecture 6 February 13, 2007 Simple Linear Regression Lets think about our problem Simple equation y = 0 + 1x + u Fitted line Residual Concept of Regression Function We started with the inherent relationship: y = 0 + 1x + u The expected valu...
Lecture 6.pptPath: Maryland >> ECON >> 422 Fall, 2008
Description: Lecture 6 February 13, 2007 Simple Linear Regression Lets think about our problem Simple equation y = 0 + 1x + u Fitted line Residual Concept of Regression Function We started with the inherent relationship: y = 0 + 1x + u The exp...
Lecture 7.pdfPath: Maryland >> ECON >> 422 Fall, 2008
Description: Lecture 7 February 22, 2007 Simple Linear Regression What do the OLS Estimators tell us? Sample covariance between x and y Sample variance of x The slope coefficient is of primary interest, as: y = 0 + 1x dy = 1 dx Mathpnl.dta When will th...
Lecture 7.pptPath: Maryland >> ECON >> 422 Fall, 2008
Description: Lecture 7 February 22, 2007 Simple Linear Regression What do the OLS Estimators tell us? Sample covariance between x and y Sample variance of x The slope coefficient is of primary interest, as: y = 0 + 1x dy = 1 dx Mathpnl.dta When will th...
Lecture 8.pdfPath: Maryland >> ECON >> 422 Fall, 2008
Description: Lecture 8 February 27, 2007 Simple Linear Regression Quick review of last class How to interpret OLS coefficients Goodness of Fit: R-Squared Assumptions of OLS: SLR1-SLR4 Use these four assumptions to prove unbiasedness of OLS Assumption concerning...
Lecture 8.pptPath: Maryland >> ECON >> 422 Fall, 2008
Description: Lecture 8 February 27, 2007 Simple Linear Regression Quick review of last class How to interpret OLS coefficients of Fit: R-Squared of OLS: SLR1-SLR4 Goodness Assumptions Use these four assumptions to prove unbiasedness of OLS Assumption co...
Lecture 9.pdfPath: Maryland >> ECON >> 422 Fall, 2008
Description: Lecture 9 March 1, 2007 Multiple Linear Regression Quick review of last class SLR5: Homoskedasticity Allows us to say OLS is BLUE Units of Measurement Functional form: how to interpret Working with more than one independent variable We want to be ...
Lecture 9.pptPath: Maryland >> ECON >> 422 Fall, 2008
Description: Lecture 9 March 1, 2007 Multiple Linear Regression Quick review of last class SLR5: Homoskedasticity Allows us to say OLS is BLUE Units of Measurement form: how to interpret Functional Working with more than one independent variable We w...
Lecture 10.pdfPath: Maryland >> ECON >> 422 Fall, 2008
Description: Lecture 10 March 6, 2007 Multiple Linear Regression Estimating the Variance Our variance formula is 2 Var ( j ) = SST j (1 R 2 ) j We need an unbiased estimate of 2 2 = Var (u ) = E (u 2 ) = ui2 n Want to replace error with residual, but need...
Lecture 10.pptPath: Maryland >> ECON >> 422 Fall, 2008
Description: Lecture 10 March 6, 2007 Multiple Linear Regression Estimating the Variance Our variance formula is 2 Var ( j ) = SST j (1 R 2 ) j We need an unbiased estimate of 2 2 = Var (u ) = E (u 2 ) = ui2 n Want to replace error with residual, b...
Lecture 11.pdfPath: Maryland >> ECON >> 422 Fall, 2008
Description: Lecture 11 March 8, 2007 Multiple Linear Regression Think Conceptually Variation in Y that can be explained by X Y X X Think Conceptually The larger the blue area, the more information is used to form the estimate; the more precise we can get it ...
Lecture 11.pptPath: Maryland >> ECON >> 422 Fall, 2008
Description: Lecture 11 March 8, 2007 Multiple Linear Regression Think Conceptually Variation in Y that can be explained by X Y X X Think Conceptually The larger the blue area, the more information is used to form the estimate; the more precise we can get it ...
Lecture 12.pdfPath: Maryland >> ECON >> 422 Fall, 2008
Description: Lecture 12 March 13, 2007 Review for Midterm Inference Midterm Review Review of Probability and Statistics Wooldridge Appendix B & C Problem Set 1 Quiz 1 Simple Linear Regression Wooldridge Chapter 2 Problem Set 2 Quiz 2 Multiple Linear Regression...
Lecture 12.pptPath: Maryland >> ECON >> 422 Fall, 2008
Description: Lecture 12 March 13, 2007 Review for Midterm Inference Midterm Review Review of Probability and Statistics Wooldridge Appendix B & C Problem Set 1 Quiz 1 Simple Linear Regression Wooldridge Chapter 2 Problem Set 2 Quiz 2 Multiple L...