...BUSINESS SCHOOL Unit of Study Outline Unit Code QBUS5001 Unit Title Quantitative Methods for Business Semester 2, 2013 Pre-requisite Units: None Co-requisite Units: None Prohibited Units: ECMT5001, QBUS5002 Assumed Knowledge and/or Skills: Basic calculus, basic concept of probability and statistics Unit Coordinator: Dr Boris Choy Address: Room 482, Merewether Building(H04), The University of Sydney NSW 2006 Email: boris.choy@sydney.edu.au Phone: 0293512787 Consultation Hours: Mondays 2pm-3pm at Room 482, H04 Class Day(s): Thursdays 6pm-9pm at Merewether Lecture Room 5, H04 Required Text / Resources: 1. Textbook: Selvanathan E.A., Selvanathan, S & Keller, G. (2011) Business Statistics, Australia & New Zealand 5th Edition. CENGAGE Learning. www.cengage.com.au/selvanathan5e 2. Online resources: Blackboard and Aplia 3. Software: MS Excel with Data Analysis Plus add-in This Guide to Unit Learning Content and Assessment MUST be read in conjunction with the Business School Student Administration Manual for information about all processes (sydney.edu.au/business/currentstudents/student_information/student_administration_manual) and the Business School unit of study common policy and implementation information that apply to every unit of study offered by the Business School (http://sydney.edu.au/business/currentstudents/policy). In determining applications and appeals relating to these matters it will be assumed that every student has taken the time to familiarise themselves...
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...Introduction to Statistics Statistical Problems 1. A pharmaceutical Co. wants to know if a new drug is superior to already existing drugs, or possible side effects. 2. How fuel efficient a certain car model is? 3. Is there any relationship between your GPA and employment opportunities? 4. If you answer all questions on a (T, F) (or multiple choice) examination completely randomly, what are your chances of passing? 5. What is the effect of package designs on sales? 6. ………………….. Question??? 1. What is Statistics? 2. Why we study Statistics? Larson & Farber, Elementary Statistics: Picturing the World, 3e 2 STA 13- SYLLABUS Instructor Phone: MsC. Pham Thanh Hieu mobile:0917.522.383, email: hieuphamthanh@gmail.com Goals of To learn how to interpret statistical summaries appearing the course in journals, newspaper reports, internet, television …..and many real-world problems. To learn about the concepts of probability and probabilistic reasoning Understand variability and sampling distributions To learn how to interpret and analyze data arising in your own work (coursework and research) STA 13- SYLLABUS Grading: - One Midterms : 30% total, multiple choice exams, closed book exam, one sheet with handwritten notes (no larger than 9 ½ x 11, two sided) is allowed - Final Exam : 50% (multiple choice + short answer exam) comprehensive; closed book exam, two sheets with handwritten notes (no larger than 9 ½ x 11, two...
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... Home College Mathematics II Statistics more... Environmental Science Weekly Assignments Week One Read the follwoing two articles http://apps.seattletimes.com/reports/sea-change/2013/sep/11/alaska-crab-industry/ http://apps.seattletimes.com/reports/sea-change/2013/sep/11/oysters-hit-hard/ Write a summary of the key findings from each article. What struck you the most, do you feel that we can overcome this issue Week Two Unit 2 Problem Set 1 page 163 - 170 Lab manual Unit 2 Exercise 1 Environmental Health (Handout) Unit 2 Lab 1 page 19 - 22 Lab Manual Week Three Unit 3 Problem Set 1 Ecosystem Diagram (PPT) Unit 3 Problem Set 2 Biogeochemical Concept Map page 173 - 174 Lab Manual Unit 3 Lab 1 Experimental Design (Handout) Week Four Unit 4 Exercise 1 Population Growth: http://www.learner.org/courses/envsci/interactives/demographics/ Unit 4 Lab 1 Initiative 522 Week Five Unit 5 Exercise 1 Trees and Carbon Handout Unit 5 Problem Set 1 Page 175 - 180 Unit 5 Problems Set 1Lab Manual Global Warming CO2 and You Applied Problem Set Unit 5 Lab 1 page 89 - 94 Global Climate Change and Automobiles Week Six Unit 6 Project Part 1 Project Proposal Unit 6 Lab 1 Waterways Presentation Week Seven Unit 7 Exercise 1 Project Feedback Unit 7 Project Part 2 Project Sources Unit 7 Lab 1 Week Eight Unit 8 Problem Set 1 Breakfast Interview page 213-216 Lab Manual Unit 8 Lab 1 Life Cycle page 33-36 Lab Manual ...
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...International A Level Further Mathematics Syllabus code 9231 For examination in June and November 2013 Contents Cambridge A Level Further Mathematics Syllabus code 9231 1. Introduction ..................................................................................... 2 1.1 1.2 1.3 1.4 Why choose Cambridge? Why choose Cambridge International A Level Further Mathematics? Cambridge Advanced International Certificate of Education (AICE) How can I find out more? 2. Assessment at a glance .................................................................. 5 3. Syllabus aims and objectives ........................................................... 7 4. Curriculum content .......................................................................... 8 4.1 Paper 1 4.2 Paper 2 5. Mathematical notation................................................................... 17 6. Resource list .................................................................................. 22 7 Additional information.................................................................... 26 . 7 .1 7 .2 7 .3 7 .4 7 .5 7 .6 Guided learning hours Recommended prior learning Progression Component codes Grading and reporting Resources Cambridge A Level Further Mathematics 9231. Examination in June and November 2013. © UCLES 2010 1. Introduction 1.1 Why choose Cambridge? University of Cambridge International Examinations (CIE) is the world’s largest provider of international qualifications. Around...
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...------------------------------------------------- Graded Assignments Unit 1 Exercise 1: Statistics and Graphing Course Objectives and Learning Outcomes In this assignment, you will interpret and graph descriptive statistics. Assignment Requirements Work in small groups to complete Problems 1-4 given in the worksheet provided by your instructor (Problems Worksheets). This is also available at the link below. Fill out one activity sheet (found at the end of the document) for each of the 4 questions. Required Resources * Statistics and Graphing (SC2730.U1.HO1) Worksheets also available at: http://esa21.kennesaw.edu/activities/stats/stats.pdf * Problems Worksheets (SC2730.U1.HO2) also available at: http://esa21.kennesaw.edu/activities/stats/problems.pdf Submission Requirements 4 completed activity sheets (1 each for Problems 1-4) Unit 1 Problem Set 1: Scientific Method Applied Problem Sets Course Objectives and Learning Outcomes In this assignment, you will outline the steps of the scientific method. Assignment Requirements Refer to the Applied Problem Sets located on pp. 153-162 of the Wagner lab manual. Use the scientific method to complete the problem sets. Answer Questions 1-6 for Problem Set 1 and questions 1-8 for Problem Set 2. Submission Requirements Use Microsoft Word for Problem Sets 1 and 2, 12-pt Times New Roman font, double-spaced. Use Microsoft Excel for graphing and charting problems in Problem Set 2. Print and submit....
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...AVU-PARTNER INSTITUTION MODULE DEVELOPMENT TEMPLATE PROBABILITY AND STATISTICS Draft By Paul Chege Version 19.0, 23rd March, 2007 C. TEMPLATE STRUCTURE I. INTRODUCTION 1. TITLE OF MODULE Probability and Statistics 2. PREREQUISITE COURSES OR KNOWLEDGE Secondary school statistics and probability. 3. TIME The total time for this module is 120 study hours. 4. MATERIAL Students should have access to the core readings specified later. Also, they will need a computer to gain full access to the core readings. Additionally, students should be able to install the computer software wxMaxima and use it to practice algebraic concepts. 5. MODULE RATIONALE Probability and Statistics, besides being a key area in the secondary schools’ teaching syllabuses, it forms an important background to advanced mathematics at tertiary level. Statistics is a fundamental area of Mathematics that is applied across many academic subjects and is useful in analysis in industrial production. The study of statistics produces statisticians that analyse raw data collected from the field to provide useful insights about a population. The statisticians provide governments and organizations with concrete backgrounds of a situation that helps managers in decision making. For example, rate of spread of diseases, rumours, bush fires, rainfall patterns, and population changes. On the other hand, the study of probability...
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...Introduction The art and science of collecting, analyzing, presenting and interpreting data to make more effective decision. A collection of numerical information is called statistics. Statistical Data: According to Horace Secrist “By statistics we mean aggregate of facts affected to a marked extent by multiplicity of causes, numerically expressed, enumerated or estimated according to reasonable standard of accuracy, collected in a systematic manner for a pre-determined purpose and placed in relation to each other”. Features of This Definition Are: * Statistics are aggregate of facts. * Statistics are affected to a marked extent by multiplicity of causes. * Statistics are numerically expressed. * Statistics are enumerated or estimated according to reasonable standard of accuracy. * Statistics are collected in a systematic manner. * Statistics are for a pre-determined purpose. * Statistics should be placed in relation to each other. Functions of Statistics: * It presents facts in definite forms. * It simplifies mass of figures. * It facilitates comparison. * It helps in formulating and testing hypothesis. * It helps in prediction and * It helps in the formulation of suitable policies. Limitations of Statistics: * It does not deal with isolated measurements. * It deals only with quantitative characteristics. * Its results are true only on average. * It is only a means. * It can be misused. ...
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...Sweden This thesis is submitted to the School of Computing at Blekinge Institute of Technology in partial fulfillment of the requirements for the degree of Master of Science in Computer Science. The thesis is equivalent to 20 weeks of full time studies. Contact Information: Author(s): Imran Ashraf Address: c/o Gulfam Abbas, Älgbacken 4 LGH 081, 37234 Ronneby, Sweden E-mail: im_qamar@yahoo.com Phone: +46 700746734 Amir Shahzed Khokhar Address: c/o Gulfam Abbas, Älgbacken 4 LGH 081, 37234 Ronneby, Sweden E-mail: amir_ask@yahoo.com Phone: +46 760811926 University advisor(s): Professor Lars Lundbarg School of Computing Blekinge Institute of Technology, Sweden External advisor(s): Magnus Vigerlöf Ericsson AB Address: Ölandsgatan 1, 371 23 Karlskrona Phone: +46 10 7140404 School of Computing Blekinge Institute of Technology Box 520 SE – 372 25 Ronneby Sweden Internet Phone Fax : www.bth.se/com : +46 457 38 50 00 : + 46 457 102 45 2 Abstract Centralized databases are becoming bottleneck for organizations that are physically distributed and access data remotely. Data management is easy in centralized databases. However, it carries high communication cost and most importantly high response time. The concept of distributing the data over various locations is very attractive for such organizations. In such cases the database is fragmented into fragments and distributed to the locations where it is needed. This kind of distribution provides local control of...
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...Decision makers make better decisions when they use all available information in an effective and meaningful way. The primary role of statistics is to to provide decision makers with methods for obtaining and analyzing information to help make these decisions. Statistics is used to answer long-range planning questions, such as when and where to locate facilities to handle future sales. Definition: Statistics is defined as the science of collecting, organizing, presenting, analyzing and interpreting numerical data for the purpose of assisting in making a more effective decision. Types of Statistics: There are two types of statistics 1. Descriptive Statistics is concerned with summary calculations, graphs, charts and tables. 2. Inferential Statistics is a method used to generalize from a sample to a population. For example, the average income of all families (the population) in the US can be estimated from figures obtained from a few hundred (the sample) families. Statistical Population: Is the collection of all possible observations of a specified characteristic of interest. An example is all of the students in BUSA 3101 course in this term. Note that a sample is a subset of the population. Variable: A variable is an item of interest that can take on many different numerical values. Types of Variables or Data: 1. Qualitative Variables are nonnumeric variables and can't be measured. Examples include gender, religious affiliation, state of birth...
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...Time * Duration of factory: July 2013 to August 2013 * Class Schedules (Activities and events) Date and Time | Event | Description | JulyTime to be placed | Issue Diagnostic tests | 1 - 2 hrs.This is used to assess the levels of the students and to highlight where improvements are need versus where they will need to be fully taught. Also to monitor their progress in the Factory Files/Records will be created and maintained for each student involved in the math factory.(Time assessment for each level may differ) | JulyTime to be placed | Consultation with parent(s) and child(ren) | 30 – 60 mins. A consultation will be held, in order for the parents and child come in. We discuss their current progress, where they need to improve and how the parents can help in their development. We also discuss their strengths and how they can harness or fine tune it.This is also where we wish to gather parent and student information in these sessions also | JulyTime to be placed | Arranging of the Classes | 60 – 90 mins. Students will be sorted in their respective grade levels and competencies: * Basics * Primary * High (split between 7,8 and 9,10,11) | JulyTime to be placed | Teaching begins | Introduction of students, register is taken and lesson begins.Class Days: * Tuesday (Basic) * Wednesday (Primary) * Thursday (High)Each group will be taught on different days and each day is two hrs. each | - Time between - | - Teaching - | - Any other activities will...
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...Plan for AFE134: Business Statistics SP1 2015 | | |Week | | | |Weeks 1-2 |Introduction to Statistics|Business Statistics (BS) (Selvanathan |Module lecture recordings & lecture |Learning Statistics and Excel in |Introduce yourself to | | | |and Data Collection |et al): Chapter 1, Chapter 2 |workbook (A1, A2, A3, A4) |Tandem (LSET), Chapter 1: |the class | | |2 Mar – 15 Mar | | | |Introduction to Microsoft EXCEL & | | | | | |Video recordings: |Set up your account to the...
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...means electronic, photocopying, recording or otherwise without prior permission of the author or publisher. Correspondence related to the syllabus should be addressed to: The Pro-Registrar Caribbean Examinations Council Caenwood Centre 37 Arnold Road, Kingston 5, Jamaica, W.I. Telephone: (876) 630-5200 Facsimile Number: (876) 967-4972 E-mail address: cxcwzo@cxc.org Website: www.cxc.org Copyright © 2008, by Caribbean Examinations Council The Garrison, St Michael BB11158, Barbados CXC 05/OSYLL 00 Contents RATIONALE. .......................................................................................................................................... 1 AIMS. ....................................................................................................................................................... 1 ORGANISATION OF THE SYLLABUS. ............................................................................................. 2 FORMAT OF THE EXAMINATIONS ................................................................................................ 2 CERTIFICATION AND PROFILE DIMENSIONS ............................................................................... 4 REGULATIONS FOR PRIVATE CANDIDATES ............................................................................... 5 REGULATIONS FOR RE-SIT CANDIDATES .................................................................................... 5 SYMBOLS USED ON THE EXAMINATION PAPERS...
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...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 changes in...
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...A COMPUTER IMPLEMENTATION OF ESTIMATED VARIANCES IN MULTI-STAGE CLUSTER SAMPLING SCHEMES L. A. Nafiu, L. Idris, A. F. Busari and A. B. Olaniyan Department of Mathematics and Statistics, Federal University of Technology, Minna, Niger State (lanconserv@yahoo.com) ABSTRACT The computation of sample variances arising from multi-stage cluster sampling schemes or designs are complex and time-consuming. This paper presents a computer software written with Java programing language for implementing some of the available formulars for estimated variances in multi-stage techniques. The software has the advantages of accessibility, cheapness, and ease of use in computing estimated variances in both one-stage, two-stage and three-stage sampling schemes. A data set for estimating number of diabetic patients in Niger state for 2005 was used for illustration. We recommend that computation involving these estimated variances be done with the aid of this software. Keywords: Software, Computation, Multi-stage, Estimated Variances, Time, Data and Diabetic Patients. Introduction Multistage sampling is where the researcher divides the population into clusters, samples the clusters, and then resample, repeating the process until the ultimate sampling units are selected at the last of the hierarchical levels (Okafor, 2002). For instance, at the top level, states may be sampled (with sampling proportionate to state population size); then cities may be sampled; then schools; then classes; and...
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...Descriptive and Inferential Statistics ________________________________________ Statistics can be broken into two basic types. The first is known as descriptive statistics. This is a set of methods to describe data that we have collected. Ex. Of 350 randomly selected people in the town of Luserna, Italy, 280 people had the last name Nicolussi. An example of descriptive statistics is the following statement : "80% of these people have the last name Nicolussi." Ex. On the last 3 Sundays, Henry D. Carsalesman sold 2, 1, and 0 new cars respectively. An example of descriptive statistics is the following statement : "Henry averaged 1 new car sold for the last 3 Sundays." These are both descriptive statements because they can actually be verified from the information provided. The second type of statistics in inferential statistics. This is a set of methods used to make a generalization, estimate, prediction or decision. Ex. Of 350 randomly selected people in the town of Luserna, Italy, 280 people had the last name Nicolussi. An example of inferential statistics is the following statement : "80% of all people living in Italy have the last name Nicolussi." We have no information about all people living in Italy, just about the 350 living in Luserna. We have taken that information and generalized it to talk about all people living in Italy. The easiest way to tell that this statement is not descriptive is by trying to verify it based upon the information provided. Ex....
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