QMB 3302 Business Analytics CRN Spring 2015 T R -- 11:00am - 12:15pm -- Lutgert Hall 2209

Transcription

1 QMB 3302 Business Analytics CRN Spring 2015 T R -- 11:00am - 12:15pm -- Lutgert Hall 2209 Elias T. Kirche, Ph.D. Associate Professor Department of Information Systems and Operations Management Lutgert College of Business Suite 3304 Phone: (239) Fax: (239) ekirche@fgcu.edu Consultation Hours M & W: 2-4 PM, T: 4-6 PM Other times by appointment About the Course The course is an introduction to Business Analytics. It covers managerial statistical tools in descriptive analytics and predictive analytics, including regression. Other topics covered include forecasting, risk analysis, simulation, data mining, and decision analysis. This course provides students with the fundamental concepts and tools needed to understand the emerging role of business analytics in organizations and shows students how to apply basic business analytics tools in a spreadsheet environment, and how to communicate with analytics professionals to effectively use and interpret analytic models and results for making better business decision. Emphasis is on applications, concepts and interpretation of results, rather than theory and calculations. Students use a computer software package for data analysis. Learning Objectives Select, understand and apply appropriate analytical tools in the analysis of quantitative and qualitative data from a variety of business scenarios. Use software package for data analysis; understand data gathering and input considerations; and be able to analyze and interpret output (graphs, tables, mathematical models, etc.) Know considerations in collecting data and selection of appropriate analysis tools; and know how to report results in a fair, objective and unbiased manner. 1

2 Course Overview This course is organized in four main content parts as indicated in the modules table below: Foundation of Business Analytics Descriptive Analytics Predictive Analytics Making Decisions Main Modules Each main part is further broken down into topics/chapters. Assignments Business Analytics involves "learning by doing" course assignments (three assignments). Course assignments involve the analysis of problems and/or cases from the textbook. Students are encouraged to submit their analysis or questions to the instructor with sufficient time for review and feedback. The analysis for all cases will be done using Microsoft Excel with the assistance of Frontline Systems Risk Solver Platform and XLMiner. Our computer lab has the required software for class instruction but, to complete assignments, you will need a personal copy installed in your personal computer which can be downloaded from Frontline Systems website. See required software section below. Pay attention to the organization and quality of your work file which may reduce your overall grade. NO LATE ASSIGNMENT WILL BE ACCEPTED. It is your responsibility to submit the document on or before the due date. Exams There will be three (3) exams. The exams are based on the three assignments and related material/chapters covered in the course. Exams are open book/notes. Note: In order to answer some of the questions in the exams, you must have completed the corresponding assignment on time. 2

3 NO MAKEUP EXAMS will be given. Only the following reasons will be considered if you miss an exam: armed services requirement, extreme health situation, and death. Any exam that is missed without an appropriate documentation will automatically receive a score of zero. Class Format, Policies, and Student Participation Attendance at all classes is expected but not considered into your grade. Organize your professional and personal affairs to allow for attendance at every class session. You are responsible for all announcements and assignments made in class by your instructor. Poor attendance is correlated with lower performance in the course and I do pass around a class attendance sign-up sheet. So it is of your interest to attend all classes. Since we will not spend class time addressing all topics and problems surveyed in your text, use your notes as a 'guide' in preparing for the exam; text material not covered in class but descriptive in nature or closely related to lecture material will be appropriate for exam purposes. Classes meet twice each week for 75 minutes. The class policies listed below is intended to give you a behavioral framework in which you can build your own personal learning objectives for this course. 1. You are expected to have completed the assigned reading for the day. 2. Assignments are individual effort. 3. Your professionalism, integrity, and academic success are at stake if you fail to submit work on time. 4. Keep cell phones turned off (or on silent) when in class and do not use computers in the lab for navigating the internet or downloading s. Grades When preparing your assignments pay attention to the content, cleanliness, and organization of the document. They all contribute to your grade. The final grade is computed as a percentage of the total points earned in three assignments (25% weight) and three exams (75% weight). Letter grades will be assigned based on the following criteria as a percentage of total points: 94 and above: A 90 to less than 93: A- 87 to less than 90: B+ 82 to less than 87: B 80 to less than 82: B- 3

4 75 to less than 80: C+ 70 to less than 75: C 65 to less than 70: D+ 60 to less than 65: D below 60: F Incomplete will be given by exception when a limited portion of the course material has not been completed by the last exam due date, in accordance with University policy published in the Catalog. The instructor on an individual basis will review each case. Required Course Material: 1. Textbook: Business Analytics by James R. Evans. Published by Pearson (customized for FGCU) Please use the following ISBN for FGCU bookstore: ISBN NOTE: the full text information is: ISBN-10: ISBN-13: Software: Microsoft Excel and Frontline System s Risk Solver Platform and XLMiner (student version) Access the companion website to gain access to important course resources (data files) and download Frontline System add-in to Excel Companion website at: Note: If you purchase a used textbook, make sure you have access to the companion website to download a copy of Frontline Systems Risk Solver Platform and XLMiner 3. Optional: You may also want to read a good book about how companies are using what we cover in this course to gain a competitive edge in the business world: Competing on Analytics - The New Science of Winning (Hardcover) by Thomas H. Davenport and Jeanne G. Harris, Harvard Business School Press. 4

5 Class Schedule The Schedule provides a map of the course. The schedule is organized by Week Number and Week Start Date so you can organize and plan your studies accordingly. The critical item to remember is that project assignment and exam due dates cannot be delayed. Week number and date 1 1/6 & 1/8 Topic Chapter 1 Description Course overview Introduction to Analytics and Excel Decision Models Problem Solving and Decision Making Excel Functions Spreadsheet Add-ins for Business Analytics Chapter 13 Decision Analysis (chap. 13) Making Decisions with Uncertain Information Review (after class): watch instructional video: Descriptive Statistical Measures (Chap. 4): IV_DS o Populations and Samples o Measures of Location, Dispersion and Shape o Measures of Association o Excel Descriptive Statistics Tool o Outliers Handout: Case 1 5

6 2 1/13 & 1/15 Chapters 13 Decision Analysis The Value of Information Decision Trees Review (after class): watch instructional video: Sampling and Estimation (Chap. 6): IV_SE o Estimating Population Parameters o Sampling Error o Sampling Distributions o Interval Estimates o Confidence Intervals o Using Confidence Intervals for Decision Making 3 1/20 & 1/22 Chapter 7 Before class: watch instructional video Statistical inference (Chap 7): IV_SI In class applications: Statistical inference Hypothesis Testing One-Sample Hypothesis Tests Two-Sample Hypothesis Tests ANOVA 4 1/27 & 1/29 Chapter 7 Before class: watch instructional video Statistical inference (Chap 7): IV_SI In class applications: Statistical inference Hypothesis Testing One-Sample Hypothesis Tests Two-Sample Hypothesis Tests ANOVA Due: case 1 Exam 1: 1/29 6

7 5 2/3 & 2/5 6 2/10 & 2/12 Chapter 9 Chapter 9 Regression Analysis Simple and Multiple Linear Regression Building Good Regression Models Regression with Categorical Independent Variables Handout: case 2 Regression Analysis Simple and Multiple Linear Regression Building Good Regression Models Regression with Categorical Independent Variables 7 2/17 & 2/19 8 2/24 & 2/26 Chapter 9 Chapter 10 Regression Analysis Forecasting Simple and Multiple Linear Regression Building Good Regression Models Regression with Categorical Independent Variables Forecasting Techniques Qualitative and Judgmental Forecasting Statistical Forecasting Models Forecasting Models for Time Series with a Linear Trend 9 3/3 & 3/5 10 3/17 & 3/19 SPRING BREAK Chapter 10 SPRING BREAK Forecasting Forecasting Time Series with Seasonality Selecting Appropriate Time-Series-Based Forecasting Methods Regression Forecasting with Causal Variables 7

8 11 3/24 & 3/ /31 & 4/2 13 4/7 & 4/9 14 4/14 & 4/ /21 & 4/23 Chapter 10 Chapter 11 Chapter 11 Chapter 12 Chapter 12 Chapter 12 Forecasting Forecasting Time Series with Seasonality Selecting Appropriate Time-Series-Based Forecasting Methods Regression Forecasting with Causal Variables Last Day to Drop/Withdraw without Academic Penalty: 3/27 Due: Case 2 Exam 2: 3/26 Simulation and Risk Analysis Simulation and Risk Analysis Spreadsheet Models with Random Variables Monte Carlo Simulation Using Risk Solver Handout: case 3 Simulation and Risk Analysis Simulation and Risk Analysis Overbooking Model Introduction to data mining The Scope of Data Mining Data Exploration and Reduction Introduction to data mining The Scope of Data Mining Data Exploration and Reduction Introduction to data mining Classification Techniques Association Rule Mining LAST DAY OF CLASS: 4/23 16 Final exam week See Gulfline for date & time Florida Gulf Coast University, in accordance with the Americans with Disabilities Act and the University s guiding principles, will provide classroom and academic accommodations to students with documented 8

9 disabilities. If you need to request an accommodation in this class due to a disability, or you suspect that your academic performance is affected by a disability, please see me or contact the Office of Adaptive Services. The Office of Adaptive Services is located in Howard Hall, room 137. The phone number is or TTY Additional assistance: The Center for Academic Achievement (CAA) offers academic support services for any FGCU student. The services are at no extra charge to students and include: peer tutoring, Supplemental Instruction, Student Success Workshops, and individualized academic coaching. If you would like to participate in or learn more about these services, please visit the CAA in Library 103. You may also the CAA at caa@fgcu.edu or call at (239) The CAA website is * This is a planned course structure and may change if necessary to meet learning goals 9