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    Linear Probability Model

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    The linear probability model‚ ctd. When Y is binary‚ the linear regression model Yi = β0 + β1Xi + ui is called the linear probability model. • The predicted value is a probability: • E(Y|X=x) = Pr(Y=1|X=x) = prob. that Y = 1 given x • Yˆ = the predicted probability that Yi = 1‚ given X • β1 = change in probability that Y = 1 for a given ∆x: Pr(Y = 1 | X = x + ∆x ) − Pr(Y = 1 | X = x ) β1 = ∆x 5 Example: linear probability model‚ HMDA data Mortgage denial v. ratio of debt payments to income (P/I

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    Comparison of the Effects of Exogenous Oil Supply Shocks on Output and Inflation in the G7 Countries. Journal of the European Economic Association‚ 6(1)‚ 78-121. Kiseok‚ L.‚ & Shawn Ni‚ B. (2002). On the Dynamic Effects of Oil Price Shocks: A Study Using Industrial Level Data. Journal of Monetary Economics‚ 49(4)‚ 823-852. Klein‚ L. R.‚ Duggal‚ V. K.‚ & Saltzman‚ C. (2005). The Sensitivity of the General Price Level to Changes in the Price of Crude Oil. Business Economics‚ 40(4)‚ 74-77. Lippi‚ F.‚

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    Simple Linear Regression

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    describe the relationship between x and y using a simple linear regression model of the form µy = β 0 + β1 x 1000 900 Sale Price (in Thousands of Dollars) 800 700 600 500 400 300 200 100 0 0 100 200 300 400 500 600 700 800 900 1000 Appraised Value (in Thousands of Dollars) response variable y : sale price explanatory variable x: appraised value relationship between x and y : linear strong positive We can estimate the simple linear regression model using Least Squares (LS) yielding the following

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    programming C

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    Advertising expense 88‚000 Indirect materials 40‚000 The company estimates that 64‚000 direct labor hours will be worked and 80‚000 machine hours will be incurred during the year. If overhead is applied on the basis of direct labor hours‚ what will be the overhead rate per hour? 2. Energetica Company’s predetermined overhead rate is based on direct labor hours. At the beginning of the current year‚ the company estimated that its manufacturing overhead would total $440

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    Intro to programming

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    Display “What is your height?” Input height 2. Design an algorithm that prompts the user to enter his or her favorite color and stores the user’s input in a variable named color. Display “What is your favorite color?” Input Color Chapter 2: Programming Exercises 1‚ 4 1. Personal Information Design a program that displays the following information: • Your name • Your address‚ with city‚ state‚ and ZIP • Your telephone number • Your college major Pseudocode: Display “Enter your name”

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    Title : Graphing a Linear Relationship Objective : To verify the linear relationship between the circumference and the diameter of circular objects by taking experimental data and utilizing graphical techniques. Introduction : The distance around a circle is called its circumference. A simple experiment can be conducted to aid in understanding the formula for the circumference of the circle. Use a piece of string to measure the distance around a circular

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    Linear Algebra Problems

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    MA2030 589 UNIVERSITY OF MORA TUW A Faculty of Engineering Department of Mathematics B. Sc. Engineering Level 2 - Semester 2 Examination: MA 2030 LINEAR ALGEBRA Time Allowed: 2 hours 2010 September 2010 ADDITIONAL MATERIAL: None INSTRUCTIONS TO CANDIDATES: This paper contains 6 questions and 5 pages. Answer FIVE questions and NO MORE. This is a closed book examination. Only the calculators approved and labeled by the Faculty of Engineering are permitted. This examination

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    Object-Oriented Programming (OOP) / Event-Driven Programming (EDP) versus Procedural Programming (PP) Name Institution Date Introduction Programming is an innovative undertaking through which programmers use computers to carry out tasks and solve problems. Programming paradigms are the various approaches to programming. Two of the most fundamental programming paradigms include object-oriented programming as well as procedural programming. Object-oriented programming employs the interaction

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    Linear Models Examples

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    Curve-Fitting Project – Linear Model: Average Sales Prices of new homes sold in the United States between 1964 and 2008 (LR-1) Purpose: To analyze the average sales prices of new homes sold in the United States from 1964 to 2008. Data: The prices were retrieved from http://www.census.gov/const/uspriceann.pdf. I chose to use the prices between 1964 and 2008 as they showed a huge increase (More data was available (see link)). Average sales prices of new homes sold in the US Year Time (seconds)

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    Java Programming

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    GE217: Composition II Week 1 – Lesson 1 – Writing Assignment Pros and Cons "The Case Against Tipping" Pros Cons Generosity‚ Sharing means caring Seems like a mandatory tax – Service already paid for Promotes good service No Discretion - Awkwardness when one doesn’t tip Primary income of employee Becoming mandatory and not an option "The Consequences of ’Carnage as Entertainment’ " Pros

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