ECO 3411: QUANTITATIVE BUSINESS TOOLS II

Transcription

1 ECO 3411: QUANTITATIVE BUSINESS TOOLS II Professor: Dr. Bradley Braun Office Hours: M & W 8-10 am Location: BAII 302Y Note: Office hours may be held online from time to time. It is always advisable to contact me via if you would like to meet face-to-face. I will also meet with students before and after class on an as needed basis. All office hours will be held online during finals week. Teaching Assistants: Runbai Wan & Amber Boyette Help Desk Hours: see Webcourses Location: BAII 303M Note: The Help Desk will be closed after the last day of class. The Help Desk is closed when exams are open. all correspondence will be handled through Webcourses. should only be used to communicate personal issues that cannot be addressed on the discussion boards in Webcourses. For a timely response, be sure to include All Teaching Assistants as recipients of your . Prerequisites: ECO 2013, ECO 2023, and either ECO 3401, or MAC 2233 and STA It is expected that students are familiar with Probability Theory, Random Variables, and Descriptive Statistics of Univariate Data, including Probability Distributions. LECTURES AND LEARNING RESOURCES This is a video streaming course. The live lectures are scheduled Monday and Wednesday from 12 noon until 13:30. The lecture will be available for viewing via Tegrity. Keep in mind that instructors have no control over the production quality or accessibility to the UCF video stream. Students encountering issues with the Lecture Capture videos should contact the UCF Help Desk at (407) PLEASE DO NOT CONTACT THE INSTRUCTOR OR TEACHING ASSISTANTS AS WE CANNOT HELP YOU. All homework submission, testing, and access to lecture captures will be done through UCF s course management system called Canvas. Tests must be taken at the Testing Center assigned by the campus in which you are registered for the class. Lectures are made available via Tegrity. All learning resources, including a text book and power point slides, are available for FREE on Screencast (see pages 6-7). COURSE DESCRIPTION ECO 3411 streamlines and focuses education in quantitative business tools to meet the needs of our graduates in the 21st century workplace. ECO 3411 concentrates on the types of data, methods, and decision making applications most useful in business. In this course, you will learn how to: Restate Problems as Models That Can Shed Light on Business Decisions Select Measurable and Appropriate Variables and Obtain Data for These Variables Choose and Apply Proper Ethical Analytical Methods to Each Applied Business Case Obtain Results and Reach Practical Conclusions from Applied Business Cases Translate Applied Business Case Findings to Business Report Form for Informed Decision Making 1

2 Lectures, projects, and exams stress understanding of the analytical tools and the interpretation of results using Applied Business Cases. There will be no required calculator drill work and no math proofs or formal derivations. Instead, this course will stress critical thinking and interactive learning to the real world of business data analysis. The proper quantitative tools must be properly and ethically applied for the results to contribute rather than confuse or misdirect the decision-maker. COURSE OBJECTIVES This course focuses on the types of data, statistical methods, and decision making tools most often used in business. The course will familiarize you with computer generated output to replace the busy work found in traditional business stat courses (plugging into canned formulas, plotting on graph paper, tabulating results, and looking up critical values in distribution tables). You ll discover how easy it is to read and interpret statistical output. The text, projects, and exams fully-integrate computer output so you will learn to perform analysis the same way business practitioners do. This course will transform you into an effective statistics user. You are here to do statistical analysis on actual Applied Business Case data. You will learn how to use the numerical result of a statistics problem to reach a realworld decision by involving you in relevant, practical, and exciting learning experiences. Ultimately, your emerging quantitative abilities will become inseparably-linked to the rest of your studies and professional preparation. Attendance and Class Activities: Because this course contains some of the most difficult concepts to master, regular viewing of lectures, learning modules, and assigned readings in the text are essential. In the class lectures and the learning modules I present new concepts and terms, I apply the concepts to problem solving in real world cases, I review and summarize previous concepts, and provide tips and point out common pitfalls. In class I will give interactive computer presentations using Minitab and Excel software. Your understanding of the class experiences will benefit by reading beforehand the assigned text materials, or by watching beforehand the supplemental learning module. ASSESSMENTS Examinations: Students must take exams at the testing center assigned by the campus at which they are enrolled. A limited time will be designated to complete each exam. The exam window will be the operating hours of your testing center. For each exam you are allowed a non-programmable calculator, a note card, and lab provided scratch paper. Please turn cell phones off in the testing lab. Exams consist of multiple choice questions typically grouped within the context of extended case applications from the business world. Most questions involve recognizing and applying terms and concepts, doing numerical computation, and interpreting computer output and graphical plots. Grading is on a curve to reflect the challenging nature of the exams. It is not unusual to see scores exceeding 100 to reward superior performers. Please note that Canvas may not be able to incorporate a curve in the grade display. There are two (2) midterm exams and a comprehensive final. Each midterm exam counts 22 percent of the course grade. The final exam is comprehensive but with heavy emphasis on material following the second midterm exam. The final counts 46 percent. Note that the comprehensive final exam is not optional. Low Score or Missed exams: It is very important to make every effort to take and perform well on both midterm exams. However, if you perform poorly or miss a midterm exam, the comprehensive final exam will be given an extra 22% weight and the lowest midterm exam grade will be dropped. There is no extra credit work available in this course and the comprehensive final exam is required! 2

3 Projects: The projects summarize and apply the concepts and problem-solving tools introduced in class and in the text. To help you prepare for each project, there is a corresponding sample project (with answers) in the assigned Case Studies book, some of which are discussed in the Learning Modules. The projects are designed to help you: 1) bridge the gap between initial learning of each new method and demonstrating mastery on the exams, 2) provide timely feedback about how well you are doing and where you need extra work, and 3) buy-into the course and its lifelong usefulness to decision-making situations. There are 12 projects, which must be completed and submitted on Webcourses. There are several versions of each project, but each student will only be permitted to attempt the version assigned to them. Projects 1-11, but not project 12, can be taken multiple times to the closing date and time, with the highest score recorded as your grade. Note that project submission may be required to access other projects and learning resources. Even though some projects have more questions than others, all will be assigned equal weight. Projects 1-11 combined count 5 percent of your grade. Project 12 counts 5 percent of your grade. Projects not completed before the due date will be assigned grades of zero. Keep in mind that instructors have no control over your access to homework or exams via Webcourses. Students encountering issues with Canvas should contact the UCF Campus Help Desk at (407) DO NOT CONTACT THE INSTRUCTOR OR TEACHING ASSISTANTS. GRADING (Note: all percentage scores are rounded to four decimal places): 90% and above A B C D and less F COURSE MANAGEMENT Course Help Desk To assist in your preparation for the exams, or for assistance with assignments, the Course Help Desk is available for individual tutorial assistance by qualified teaching assistants. The teaching assistants will provide assistance face-to-face and will monitor the Discussion Boards. Course Help Desk hours will be posted on Webcourses. Webcourses The course management system is Canvas, which is operated, managed and maintained by the University. Discussion Board: Both the instructor and teaching assistants monitor the discussion boards on Canvas. Please be specific when writing the subject line on a Discussion Post so that other students can participate in the discussion and as an index to quickly check to see if a question has been asked and answered. The use of the discussion board or any other network platform to communicate any information about an assignment or quiz is cheating. Announcements: Students are responsible for all information posted to the Announcement Board on Canvas. All correspondence will be done in Canvas, and should be used sparingly to communicate items of a personal nature. It is not to be used to mass the entire class for any reason. To ensure for a more timely response to an be sure to copy the Teaching Assistants. Grade Display: Canvas has a grade display, which allows you to monitor your progress in the course. Keep in mind that Canvas may only display your raw scores. To help monitor your grade, I will supply a simple grade calculator that you can plug in your raw scores from Canvas. Social media: TAs must be members of all media groups, such as Facebook, that are set up for this class. Chat Room: Real time discussion with TAs and instructor. See Canvas for dates and times. 3

4 IMPORTANT POLICIES Cyber bullying, cheating, and non-course related postings on the discussion boards, or mass ing the class is not tolerated. Students who violate the above protocol or UCF s Golden Rule and Code of Conduct on Webcourses will have their final grade lowered by a minimum of one full letter grade. UCF s Golden Rule and Code of Conduct can be found at DO NOT CONTACT THE INSTRUCTOR OR TEACHING ASSISTANTS TO REPORT PROBEMS WITH CANVAS OR TEGRITY. Students encountering technological issues must call the University help desk: for issues with Canvas, Tegrity and Lecture Captures call (407) If you have missed assignments owing to failure of UCF s course management system Canvas, you must provide documentation from the UCF Campus Help Desk or your testing lab. Requests for makeup assessments will be considered on a case-by-case basis. Office hours may be held online. If you would like a face-to-face meeting, please let me know via Canvas when you will be coming. However, during finals week all office hours will be held online, and the Help Desk is closed. Accommodations for students with disabilities are managed by the University. The Student Disability Services office is located in Ferrell Commons, Room 185 and is accessible online at The Office of Student Rights and Responsibilities will be notified of any instance of academic misconduct deemed to have occurred inside or outside of the classroom. Students are strongly encouraged to read the Golden Rule Student Handbook regarding academic misconduct and their rights and responsibilities as they pertain to academic misconduct. The Office of Student Rights and Responsibilities is located in Ferrell Commons, Room 227 and is accessible online at The Golden Rule Student Handbook is available online at 4

5 TOPIC OUTLINE, ASSIGNED READINGS, AND SCHEDULE *ALL DATES ARE TENTATIVE Topics Covered Text Readings to Prepare for Classes Tentative Dates* Unit I: Descriptive Data Analysis Course overview 1/6 Statistics and Data Chapter 1 and 2 1/8 Defining, Organizing, Summarizing, and Displaying Data Chapters 2 and 3; Chapter 4 section 1 1/13 Project Due** Summarizing Data with Regression Chapter 4 1/15 Holiday: Martin Luther King 1/20 Fitting the Regression Equation Chapter 4, Chapter 5 sec 1 1/22 Project 1 Multiple Regression Chapter 4 1/27 Project 2 Unit I Review Exam I preparation 1/29 Project 3 UNIT I EXAM: opens 13:30 Wednesday 1/29- closes 23:59 Thursday 1/30 Unit II: Inferential Statistics Sampling and Inference Chapter 7 2/3 Sampling Distributions Chapter 6, Chapter 8 2/5 One Sample Estimation Chapter 9 sec 1-3 2/10 One Sample Testing Chapter 9 sec 4-7 2/12 One Sample Testing and Estimation Chapter 9 sec 1-7 2/17 Project 4 Matched Paired Sample Testing Chapter 9 sec 8 2/19 Project 5 Testing Regression Analysis Chapter11 sec 2 Unit II Review Exam II preparation 2/24 Project 6 UNIT II EXAM: opens 13:30 Monday 2/24- closes 23:59 Wednesday 2/26 Spring Break: 3/3-3/7 Withdrawal Deadline: 3/18 Unit III: Advanced Topics Regression: Model Building Chapter 11 sec 1-2 3/10-3/12 Regression: Multicollinearity Chapter 11 sec 3-4 3/17 Regression: Specification Bias Chapter 11 sec 1-4 3/19 Regression: F-Test for Model Significance Chapter 11 sec 5-6 3/24 Project 7 Regression: Prediction and Forecasting Chapter 11 sec 7-9 3/26-3/31 Regression Review Chapters 4 and 11 4/2 Analysis of Variance for Experimental Chapter 10 4/7-4/9 Projects 8 & 9 Design Models Nonparametric Statistics: Sign and Sign- Rank vs. Parametric Tests Chapter 12 4/14-4/16 Project 10 Unit III Review Exam III preparation 4/21 Projects 11&12 UNIT III EXAM: opens 13:30 Monday 4/21- closes 20:00 Thursday 4/24 *ALL DATES ARE TENTATIVE. **All Projects are due before 7 a.m. of the first date shown above. The due dates are shown in Webcourses and are strictly observed. Access to some projects and the practice exams are dependent on timely project submission. 5

6 LEARNING RESOURCES Course materials are housed on Screencast, which is a non-ucf server. These course materials have a value of over $300 but are available for download FREE to registered students in Quantitative Business Tools II UCF-COBA. The supplemental learning modules cover the same material as the assigned readings and class lectures. There are additional supplemental video clips in each unit. A sample project for each assigned project can be found in the supplemental videos. For each lecture title there is a supplemental video clip and the associated power point slide show, both of which are housed in the same folder. To access course materials on Screencast, copy and paste the URL into your browser and then enter the password, which is case sensitive. The learning resources available for download Free to students enrolled in the course include: 1. Required Text: Business Statistics and Applications, 2012 draft, by Mark D. Soskin and Bradley Braun. Free to students enrolled in the course and available for download. 2. Supplemental Learning Modules: The supplemental learning modules cover in an annotated format the course content from the class lecture and assigned readings in the text. Free to students enrolled in the course and available for download. 3. Study Guide: Review and case study questions, 2012 Draft. Free to students enrolled in the course and available for download. 4. Case Studies: Sample Projects (with answers), 2012 Draft. Some of these are also covered in the supplemental learning modules. Free to students enrolled in the course and available for download. 5. Practice Exams: Past Exams with detailed explanations on how to solve each problem. Free to students enrolled in the course and available for download. 6. Data: All data are provided Free to students enrolled in the course and available for download. Recommended Software: Software packages are not required. However, if you would like to follow along with the examples, you will need to install the appropriate software on your computer. The two software packages used in the class are Minitab 16 and Microsoft Excel. See video for setting up and using the software packages. Minitab can be rented for about $30 for the semester. All COBA computers have Microsoft Excel installed. Note that Excel cannot perform all of the statistical modeling we will be doing in this class. Please note that course materials are not for resale or any other commercial use. All intellectual materials housed on Screencast are the sole property of the authors. These course materials are available Free to registered students in order to maximize their learning of business statistics. 6

7 Title URL Password Tutorial on Installing and Using Software No Password Necessary Installing and using Minitab and Excel for statistical analysis Learning Resources Free Book Text, Study Guide, Case Studies, Practice Exams, Syllabus, Data 1.Statisitcs and Data Unit I: Descriptive Statistics Unit I 2.Defining,Organizing,Summarizing and Displaying Data 3.Summarizing Data with Regression 4.Fitting the Regression Equation 5.Multiple Regression Unit II: Inferential Statistics Unit II 6. Sampling and Inference 7.Sampling Distributions 8.One Sample Estimation 9.One Sample Testing 10.Matched Pair Sample Testing 11.Testing Regression Analysis Unit III: Advanced Topics Unit III 12.Regression Model Building and Specification 13.Regression Models and Multicollinearity 14.Regression Models and Specification Bias 15.Regression Models and the F-Test for Significance 16.Prediction and Prediction Intervals 17. Evaluating a Forecasting Model s Performance 18. Experimental Design and ANOVA 19. Nonparametric Methods 7