CS229 Lecture notes Andrew Ng Supervised learning Lets start by talking about a few examples of supervised learning problems. Suppose we have a dataset giving the living areas and prices of 47 houses from Portland‚ Oregon: Living area (feet2 ) 2104 1600 2400 1416 3000 . . . Price (1000$s) 400 330 369 232 540 . . . We can plot this data: housing prices 1000 900 800 price (in $1000) 700 600 500 400 300 200 100 0 500 1000 1500 2000 2500 3000
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Copa Cruises - Welcome Aboard! Copa Cruises is a 40-year old company that offers dining and sightseeing cruises. What started with only one ship at Maryland’s Eastern Shore‚ is now a big business operating at multiple locations with 40 vessels. Copa operates scheduled tours at least twice daily during the peak travel/tourism seasons at each of its locations. The total number of scheduled tours varies based on the number of vessels available at each location. Copa also offers its ships exclusively
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enactment of the Sarbanes-Oxley Act. We begin with a sample of firms with internal control weaknesses and‚ based on industry‚ size‚ and performance‚ match these firms to a sample of control firms without internal control weaknesses. Our conditional logit analyses indicate that a relation exists between audit committee quality‚ auditor independence‚ and internal control weaknesses. Firms are more likely to be identified with an internal control weakness‚ if their audit committees have less financial
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Introduction to Stata Christopher F Baum Faculty Micro Resource Center Boston College August 2011 Christopher F Baum (Boston College FMRC) Introduction to Stata August 2011 1 / 157 Strengths of Stata What is Stata? Overview of the Stata environment Stata is a full-featured statistical programming language for Windows‚ Mac OS X‚ Unix and Linux. It can be considered a “stat package‚” like SAS‚ SPSS‚ RATS‚ or eViews. Stata is available in several versions: Stata/IC
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Chapter 9 Na¨ve Bayes ı David J. Hand Contents Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Algorithm Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Power Despite Independence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Extensions of the Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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Validity- does the variable accurately reflect the phenomenon you are trying to measure. Reliability- does the indicator consistently assign the same number. Cross-sectional data- no time/multiple entries. Panel data set- multiple entries/over time. Time series-one entry/time. Population: the total set of items or people that a researcher is interested in studying. Sample: a subset of the population- random or nonrandom. Goal is to be representative of population.Criteria for evaluating causal relationships
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2) Basic Ideas of Linear Regression: The Two-Variable Model In this chapter we introduced some fundamental ideas of regression analysis. Starting with the key concept of the population regression function (PRF)‚ we developed the concept of linear PRF. This book is primarily concerned with linear PRFs‚ that is‚ regressions that are linear in the parameters regardless of whether or not they are linear in the variables. We then introduced the idea of the stochastic PRF and discussed in detail the nature
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Pacific-Basin Finance Journal 9 Ž2001. 1–27 www.elsevier.comrlocatereconbase The market effects of CEO turnover in Australian firms Jo-Ann Suchard a‚) ‚ Manohar Singh b‚ Robert Barr c a School of Banking and Finance‚ UniÕersity of New South Wales‚ New South Wales 2052‚ Australia b Long Island UniÕersity‚ New York‚ USA c Commonwealth Bank of Australia‚ Australia Abstract We examine the relationship between the monitoring of CEOs by inside and outside directors and CEO turnover in the Australian
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SPRING CLEANING: RURAL WATER IMPACTS‚ VALUATION‚ AND PROPERTY RIGHTS INSTITUTIONS∗ MICHAEL KREMER JESSICA LEINO EDWARD MIGUEL ALIX PETERSON ZWANE I. INTRODUCTION Movement toward private property rights institutions has been called critical to successful economic development (De Soto 1989; North 1990). Yet social norms and formal laws often create communal property rights in natural resources. In Islamiclaw‚ for ∗ This research is supported by the Hewlett Foundation‚ USDA/Foreign Agricultural
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SIMULATION MODEL FOR EMERGENCY DEPARTMENT ABSTRACT The paper presents a comprehensive research study on the Simulation Model for Emergency Department. The study was conducted in the Emergency Department (ED) at The Ohio State Medical Center. A simulation model was developed using Arena (7.0) to model the process flow of patients in order to analyze the ED System performance. A Statistical Design of Experiments study was performed to study the significance/ non significance
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