responsibility program. The goal of the program is to rebuild the confidence of investors in our capital markets and reestablish audited financial statements as a clear picture window into corporate America. SAS No. 99 requires you to gather and consider a great deal of information to assess fraud risks. SAS 99 defines fraud as an intentional act that results in a material misstatement in financial statements. An audit requires due professional care‚ which in turn requires that the auditor exercise professional
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always rounds down to the nearest Canadian dollar‚ in order to make a profit. How many Canadian dollars do I get back? How much profit does she make? 7. Solve for x: 8. The following chart represents a survey done on cellphone use as shown. | Cellphone | No Cellphone | Total | Under 25 | 600 | 100 | | 25 or over | 260 | 320 | | Total | | | | If a person is selected at random from those polled‚ determine the
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Proposition of fact: Cellphones are bad for human’s health. Definition: A. Cellphone: Cellular telephone a portable telephone operated by cellular radio. B. Bad: Having undesirable or negative qualities and capable of harming. C. Health: the general condition of the body or mind with reference to soundness and vigor. From: Dictionary.com Source: 1. Cellphone can increase cancer risk. Danielle Dellorto “Cell phone use can increase possible cancer risk” CNN Health 31 May‚ 2011. A team
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PABASA SA NUTRITION: Its effectiveness on the knowledge‚ attitudes and practices as acquired by mothers of selected Barangays in Hindang Leyte. INTRODUCTION: Nutrition is recognized as a basic human right‚ vital to the survival‚ growth and development of children according to the United Nations Children’s Fund (UNICEF). And proper nutrition is a key to having a happy‚ healthy life‚ but despite this pronouncement‚ millions of people around the world suffer from malnutrition and continues to
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HARMFUL AND DETRIMENTAL EFFECTS IN CELLPHONE USAGE In recent years‚ mobile telecommunication systems have grown significantly‚ to the point where more than a sixth of the world’s population uses mobile phones. By the end of 2004‚ more than a billion subscribers across more than 200 countries were estimated to be using mobile phones The development of mobile communications has moved rapidly. In the 1980s‚ first generation mobile phones‚ using analogue technology‚ allowed the transmission of
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MIS 6324 Business Intelligence 3. Classification using SAS Enterprise Miner In this question you will analyze the JUNKMAIL dataset found in the SASHELP library. Follow the procedure we used for analyzing the HMEQ dataset. Detailed instructions for the HMEQ analysis are given in the emcs.pdf document. You will need to create and execute the process flow diagram shown above. Further requirements for analyzing JUNKMAIL are as given below: This data will be used to classify emails as junk mail
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Zestha Faith Marie Peñol Sumbanon M.H del Pilar St..Jaro‚Iloilo City Mobile Number: 0946-2848586 E-mail Address: szesthafaith@yahoo.com JOB OBJECTIVE: “To serve the company to the best of my ability with sincerity and dedication” PERSONAL INFORMATION Nickname Zes Age 20 Sex Female Date of Birth August 24‚ 1992 Place of Birth Jaro‚ Iloilo City Civil Status Single Citizenship Filipino Height 5 feet 6 inches Weight 115 lbs. Religion Roman
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Logistic Regression Using SAS For this handout we will examine a dataset that is part of the data collected from “A study of preventive lifestyles and women’s health” conducted by a group of students in School of Public Health‚ at the University of Michigan during the1997 winter term. There are 370 women in this study aged 40 to 91 years. Description of variables: Variable Name Description Column Location IDNUM Identification number 1-4 STOPMENS 1= Yes‚ 2=
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"E:\regression"; run; proc import datafile ="E:\regression\pizza.csv" out = bas.pizza dbms= csv replace; run; A Few Case Studies Solved Page # 2 A Few Case Studies Solved 2. Checking for correlation ods html; /*codes for correlation*/ SAS output for correlation Variable Sales Boys Adcosts Outlets Varieties Competitor Custmer N 15 15 15 15 15 15 15 Mean 24.20000 6.06667 11.06667 14.86667 13.66667 3.40000 29.93333 Simple Statistics Std Dev Sum 21.91281 363.00000 4.51136 91.00000 4.75795
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Utah News Center‚ “We found that people are as impaired when they drive and talk on a cell phone as they are when they drive intoxicated at the legal blood-alcohol limit.” Many people talk about how bad drunk drivers are yet they still use their cellphones‚ which is equivalent to having the legal blood-alcohol limit. Similar to the points presented by the University of Utah News Center‚ author Brian Handwerk explains another reason on how using cell phones can put other drivers at risk. In Brain Handwerk’s
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