...COMM 291 Midterm Review Package Prepared by Angelica Cabrera 1. INTRODUCTION TO DATA AND VARIABLES Categorical vs. Quantitative Data Categorical Limited number – distinct categories No Quantitative Large number Yes Possible values for variable Measurement units? EXAMPLE. Which variables are quantitative and which are categorical? Employee # Age (years) Annual Income (in Performance 1,000s of dollars) Rating (1-5 scale) 5543 48 50 – 100 4.5 2431 34 20 – 49 3.9 7281 31 0 – 19 3.4 Job Type Management Clerical Maintenance 2. SURVEYS AND SAMPLING Population: _______ individuals with a common characteristic that you want to generalize about Parameter: fact or characteristic about _____________ Sample: ________ of population Statistic: fact or characteristic about ______________ EXAMPLE. Mattel claims that less than 5% of all its Hot Wheels toys are defective. When testing 100 Hot Wheels toys from a production run of 7000 toys, 7% were found to be defective. What is the: a) Population? c) Parameter? Poor (Biased) Sampling Convenience sampling: Choosing respondents that are __________ to obtain Voluntary response: Respondents volunteer, so those with __________ opinions are more likely to respond b) Statistic? d) Sample? Sampling Designs 1. Simple Random Sampling (SRS): Every individual has an equal chance of being selected 2. Stratified Random Sampling: Divide population into ______________ subgroups and randomly select from each stratum 3. Cluster Random...
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...TI-84 Plus TI-84 Plus Silver Edition Guidebook Important Information Texas Instruments makes no warranty, either express or implied, including but not limited to any implied warranties of merchantability and fitness for a particular purpose, regarding any programs or book materials and makes such materials available solely on an "as-is" basis. In no event shall Texas Instruments be liable to anyone for special, collateral, incidental, or consequential damages in connection with or arising out of the purchase or use of these materials, and the sole and exclusive liability of Texas Instruments, regardless of the form of action, shall not exceed the purchase price of this product. Moreover, Texas Instruments shall not be liable for any claim of any kind whatsoever against the use of these materials by any other party. © 2005 Texas Instruments Incorporated Windows and Macintosh are trademarks of their respective owners. ii USA FCC Information Concerning Radio Frequency Interference This equipment has been tested and found to comply with the limits for a Class B digital device, pursuant to Part 15 of the FCC rules. These limits are designed to provide reasonable protection against harmful interference in a residential installation. This equipment generates, uses, and can radiate radio frequency energy and, if not installed and used in accordance with the instructions, may cause harmful interference to radio communications. However, there is no guarantee that interference...
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...A Statistical Perspective on Data Mining Ranjan Maitra∗ Abstract Technological advances have led to new and automated data collection methods. Datasets once at a premium are often plentiful nowadays and sometimes indeed massive. A new breed of challenges are thus presented – primary among them is the need for methodology to analyze such masses of data with a view to understanding complex phenomena and relationships. Such capability is provided by data mining which combines core statistical techniques with those from machine intelligence. This article reviews the current state of the discipline from a statistician’s perspective, illustrates issues with real-life examples, discusses the connections with statistics, the differences, the failings and the challenges ahead. 1 Introduction The information age has been matched by an explosion of data. This surfeit has been a result of modern, improved and, in many cases, automated methods for both data collection and storage. For instance, many stores tag their items with a product-specific bar code, which is scanned in when the corresponding item is bought. This automatically creates a gigantic repository of information on products and product combinations sold. Similar databases are also created by automated book-keeping, digital communication tools or by remote sensing satellites, and aided by the availability of affordable and effective storage mechanisms – magnetic tapes, data warehouses and so on. This has created a situation...
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...impending accident, this control enables him to adjust the total amount of risk facing the car’s occupants and how that risk is distributed. In other words, his maneuvers will have allocative and distributive effects on the occupants’ risk. The driver’s distributive choices reveal his relative preferences for himself over his passengers. The manifestation of injuries amongst the occupants allows observation of those relative preferences. A theory of spousal altruism – indeed any romantic notion of marriage – would predict that a husband is more willing to sacrifice himself for his passenger when the passenger is his wife.2 The central purpose of this paper is to test this prediction. We compare the probability that drivers travelling with spouses sacrifice their own life to the probability that drivers traveling with other women sacrifice their own life to estimate...
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...Target Financial Reporting Quality and M&A Deals that Go Bust* HOLLIS A. SKAIFE, University of Wisconsin–Madison DANIEL D. WANGERIN, Michigan State University 1. Introduction This study investigates whether target firms’ financial reporting quality affects the likelihood that merger and acquisition (M&A) deals will ultimately be terminated. Managers looking to increase their market share, enter new markets, or diversify their operations will consider acquiring another company based on the company’s performance, geographic locations, and lines of business, respectively. If the potential target is a U.S. publicly traded company, an acquirer’s initial assessment of the expected benefits associated with the acquisition of the company is based on publicly available information. Generally, the acquirer obtains limited private information from the target prior to the signing of the acquisition agreement. Although an acquisition agreement creates a binding contractual obligation for both entities to go forward with the deal, it does not guarantee completion of the deal. The acquisition agreement typically contains a warranty by the target that its financial statements are prepared in accordance with generally accepted accounting principles (GAAP). If this warranty is breached, the deal can be terminated. We hypothesize that low-quality financial reporting by target firms prior to the announcement of a deal increases the likelihood that a target firm’s U.S. GAAP warranties stated in the acquisition...
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...RESTORING TRUST AFTER FRAUD: DOES CORPORATE GOVERNANCE MATTER? David B. Farber The Eli Broad Graduate School of Management Michigan State University N232 Business College Complex East Lansing, MI 48824-1122 e-mail: farberd@msu.edu (517) 432-0615 First Draft: January 2003 Current Draft: January 7, 2004 This paper is adapted from my dissertation completed at Cornell University. I would like to thank my committee chairperson, Julia D’Souza, for her unwavering support and guidance in the development of this paper. I also thank my other committee members - Charles Lee, Tim Mount, and Bhaskaran Swaminathanas well as Daniel Beneish, Walt Blacconiere, Tom Dyckman, John Elliott, Sue Haka, Marilyn Johnson, Tom Linsmeier, Kathy Petroni, Mike Shields, and workshop participants at The University of California at Berkeley, Cornell University, Georgia State University, Indiana University, Michigan State University, The University of Nebraska, New York University, and Syracuse University for their suggestions and comments. I appreciate the valuable comments I received at the 2002 AAA meeting. I thank Mark Beasley for sharing his sample of fraud firms. I am also grateful to the librarians at Cornell and the University of Rochester for their invaluable assistance, with special thanks to Don Schnedeker. I thank I/B/E/S for analyst data. I thank the editor and two anonymous reviewers for helpful suggestions that have greatly improved this paper. Finally, I acknowledge the financial support...
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...Weak form Efficiency and Calendar Anomalies: Comparison between Developed and Developing Equity Markets Syed Zulfiqar Ali Shah Assistant Professor-Finance, Department of Business Administration Faculty of Management Sciences, International Islamic University Islamabad E-mail: zulfiqar.shah@gmail.com Muhammad Husnain Ph.D Scholar (Finance) Mohammad Ali Jinnah University Islamabad Email: Husnain_ctn@yahoo.com Abstract Financial economists have continuously questioned the efficient market hypothesis especially in last decade. Major part of discussion is whether the equity markets are efficient and if not then up to what extent one can forecast the meaningful future movement of equity prices. On one side there are believers of random walk and contrary there are followers of chartist theories. Those who negate the random walk suggested that there exist anomalies in the equity markets and hence are not perfectly efficient. The major objective of this study is to check the weak form of efficiency and presence of calendar anomalies in equity markets of developing and developed countries. On the basis of most recent and relatively longer horizon (14 Year) data on daily basis and a range of powerful econometrics this study suggested that in broader sense both of developed and developing equity markets are weak form inefficient. Hence there is no remarkable difference in term of market efficiency in equity markets of developed and developing countries. Hence one can reject the random walk...
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...C H A P T E R 6 The Normal Distribution Objectives After completing this chapter, you should be able to Outline Introduction 6–1 Normal Distributions 1 2 3 4 5 6 7 Identify distributions as symmetric or skewed. Identify the properties of a normal distribution. Find the area under the standard normal distribution, given various z values. Find probabilities for a normally distributed variable by transforming it into a standard normal variable. Find specific data values for given percentages, using the standard normal distribution. Use the central limit theorem to solve problems involving sample means for large samples. Use the normal approximation to compute probabilities for a binomial variable. 6–2 Applications of the Normal Distribution 6–3 The Central Limit Theorem 6–4 The Normal Approximation to the Binomial Distribution Summary 6–1 300 Chapter 6 The Normal Distribution Statistics Today What Is Normal? Medical researchers have determined so-called normal intervals for a person’s blood pressure, cholesterol, triglycerides, and the like. For example, the normal range of systolic blood pressure is 110 to 140. The normal interval for a person’s triglycerides is from 30 to 200 milligrams per deciliter (mg/dl). By measuring these variables, a physician can determine if a patient’s vital statistics are within the normal interval or if some type of treatment is needed to correct a condition and avoid future illnesses. The question then is,...
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...Acceptance of Evolution and Support for Teaching Creationism in Public Schools: The Conditional Impact of Educational Attainment JOSEPH O. BAKER Department of Sociology and Anthropology East Tennessee State University Public acceptance of evolution remains low in the United States relative to other Western countries. Although advocates for the scientific community often highlight the need for improved education to change public opinion, analyses of data from a national sample of American adults indicate that the effects of educational attainment on attitudes toward evolution and creationism are uneven and contingent upon religious identity. Consequently, higher education will only shift public attitudes toward evolution and away from support for teaching creationism in public schools for those who take non-“literalist” interpretive stances on the Bible, or to the extent that it leads to fewer people with literalist religious identities. Keywords: evolution, creationism, religious identity, education, science and religion, public policy. INTRODUCTION Acceptance of evolution and support for creationism has been publicly debated since the initial diffusion of Darwin’s theory about the origin of species, particularly in the United States (Numbers 1998, 2006). From before the infamous Scopes Trial (see Larson 1997) to the present, many Americans have resisted ideas about evolution, leading to a relatively low global ranking on public acceptance of the theory...
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...ELDER ABUSE IN NURSING HOMES: THE IMPACT OF DEMENTIA/SPECIAL CARE UNITS BY CHRISTINA KAY FALK THESIS Submitted in partial fulfillment of the requirements for the degree of Master of Science in Community Health in the Graduate College of the University of Illinois at Urbana-Champaign, 2013 Urbana, Illinois Adviser: Stephen J. Notaro, Ph.D. ii ELDER ABUSE IN NURSING HOMES: THE IMPACT OF DEMENTIA/SPECIAL CARE UNITS By: Christina K. Falk Elder abuse is a topic that impacts everyone in America at some point in their life. Special care units also called dementia units are protected areas in a nursing home that are specially designed for dementia/Alzheimer patients. This thesis reviewed how a special care unit in a nursing home affect the number and severity of deficiencies reported to Medicare. The data was collected from Medicare’s Nursing Home Compare system and the Illinois Public Health Department. This study reviewed 770 nursing homes in Illinois were reviewed, 141 had special care units during the time of data collection. The facilities had a range of total deficiencies from one to 74 with Level of Harm ratings ranging from one to four on a four-point scale. The results showed that residents in a nursing facility that has a special care unit are at a greater risk of a higher Level of Harm but no difference in the number of deficiencies. Possible causes of this greater risk are due to the intrinsic nature of the population in special care units, the need for policy and procedural...
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...2014-2015 Undergraduate Academic Calendar and Course Catalogue Published June 2014 The information contained within this document was accurate at the time of publication indicated above and is subject to change. Please consult your faculty or the Registrar’s office if you require clarification regarding the contents of this document. Note: Program map information located in the faculty sections of this document are relevant to students beginning their studies in 2014-2015, students commencing their UOIT studies during a different academic year should consult their faculty to ensure they are following the correct program map. i Message from President Tim McTiernan I am delighted to welcome you to the University of Ontario Institute of Technology (UOIT), one of Canada’s most modern and dynamic university communities. We are a university that lives by three words: challenge, innovate and connect. You have chosen a university known for how it helps students meet the challenges of the future. We have created a leading-edge, technology-enriched learning environment. We have invested in state-of-the-art research and teaching facilities. We have developed industry-ready programs that align with the university’s visionary research portfolio. UOIT is known for its innovative approaches to learning. In many cases, our undergraduate and graduate students are working alongside their professors on research projects and gaining valuable hands-on learning, which we believe is integral...
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...Jim Albert and Ruud H. Koning (eds.) Statistical Thinking in Sports CRC PRESS Boca Raton Ann Arbor London Tokyo Contents 1 Introduction Jim Albert and Ruud H. Koning 1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.1 Patterns of world records in sports (2 articles) . . . . . . . 1.1.2 Competition, rankings and betting in soccer (3 articles) . . 1.1.3 An investigation into some popular baseball myths (3 articles) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.4 Uncertainty of attendance at sports events (2 articles) . . . 1.1.5 Home advantage, myths in tennis, drafting in hockey pools, American football . . . . . . . . . . . . . . . . . . . . . 1.2 Website . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . Reference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Modelling the development of world records in running Gerard H. Kuper and Elmer Sterken 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . 2.2 Modelling world records . . . . . . . . . . . . . . 2.2.1 Cross-sectional approach . . . . . . . . . . 2.2.2 Fitting the individual curves . . . . . . . . 2.3 Selection of the functional form . . . . . . . . . . 2.3.1 Candidate functions . . . . . . . . . . . . . 2.3.2 Theoretical selection of curves . . . . . . . 2.3.3 Fitting the models . . . . . . . . . . . . . . 2.3.4 The Gompertz curve in more detail...
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...any mechanism for verifying whether desirable system they will be temporarily violated, perhaps as a result of properties can be achieved. Examples of such properties failure or during system initialization. include: i) a reliable transport eventually delivers all mesExisting software model checkers cannot verify live- sages even in the face of network losses and delays, ii) all ness because doing so requires finding an infinite exe- nodes eventually join an overlay, and, iii) a distributed tree cution that never satisfies one or more liveness proper- partitioned into two halves can eventually merge. These ties. We present algorithms to find liveness violations with global liveness requirements specify that, in the limit, the high probability and the critical transition that moves the system...
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...How did increased competition affect credit ratings? Bo Becker Todd Milbourn Working Paper 09-051 Copyright © 2008, 2009, 2010 by Bo Becker and Todd Milbourn Working papers are in draft form. This working paper is distributed for purposes of comment and discussion only. It may not be reproduced without permission of the copyright holder. Copies of working papers are available from the author. How did increased competition affect credit ratings? Draft Date: September 15, 2010 Bo Becker and Todd Milbourn* Abstract. The credit rating industry has historically been dominated by just two agencies, Moody’s and S&P, leading to longstanding legislative and regulatory calls for increased competition. The material entry of a third rating agency (Fitch) to the competitive landscape offers a unique experiment to empirically examine how in fact increased competition affects the credit ratings market. Increased competition from Fitch coincides with lower quality ratings from the incumbents: rating levels went up, the correlation between ratings and market-implied yields fell, and the ability of ratings to predict default deteriorated. We offer several possible explanations for these findings that are linked to existing theories. Key words: Credit ratings; competition and reputation; information quality * Harvard Business School (Becker) and Washington University in St Louis (Milbourn). Contact author’s e-mail address: bbecker@hbs.edu. We wish to thank Pierluigi Balduzzi...
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...Transforming Lives Communities The Nation …One Student at a Time Disclaimer Academic programmes, requirements, courses, tuition, and fee schedules listed in this catalogue are subject to change at any time at the discretion of the Management and Board of Trustees of the College of Science, Technology and Applied Arts of Trinidad and Tobago (COSTAATT). The COSTAATT Catalogue is the authoritative source for information on the College’s policies, programmes and services. Programme information in this catalogue is effective from September 2010. Students who commenced studies at the College prior to this date, are to be guided by programme requirements as stipulated by the relevant department. Updates on the schedule of classes and changes in academic policies, degree requirements, fees, new course offerings, and other information will be issued by the Office of the Registrar. Students are advised to consult with their departmental academic advisors at least once per semester, regarding their course of study. The policies, rules and regulations of the College are informed by the laws of the Republic of Trinidad and Tobago. iii Table of Contents PG 9 PG 9 PG 10 PG 11 PG 11 PG 12 PG 12 PG 13 PG 14 PG 14 PG 14 PG 14 PG 15 PG 17 PG 18 PG 20 PG 20 PG 20 PG 21 PG 22 PG 22 PG 22 PG 23 PG 23 PG 23 PG 23 PG 24 PG 24 PG 24 PG 24 PG 25 PG 25 PG 25 PG 26 PG 26 PG 26 PG 26 PG 26 PG 26 PG 27 PG 27 PG 27 PG 27 PG 27 PG 27 PG 28 PG 28 PG 28 PG 28 PG 28 PG 33 PG 37 Vision Mission President’s...
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