QMB 3302 Business Analytics CRN Fall 2014

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1 QMB 3302 Business Analytics CRN Fall 2014 Instructor: Dr. Rajesh Srivastava Office: LH 3355 Hours: Tuesday and Thursday 11:00-1:30, and by appointment, Voice/ anytime. Phone: Office: 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 decisions. 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(s) for data analysis; understand data gathering and input considerations; and be able to analyze and interpret outputs (graphs, tables, mathematical models, etc.). Know the considerations in collecting data and selection of appropriate analysis tools; and know how to report results in a fair, objective, and unbiased manner. Course Overview 1

2 This course is organized in four main content parts that are to be completed in sequence as indicated in the modules table below: Part 1: Foundation of Business Analytics Part 2: Descriptive Analytics Part 3: Predictive Analytics Part 4: Making Decisions Main Modules Each main part is further broken down into topics/chapters. For example, Part 1 includes chapter 1 introducing the course material and chapter 2 which introduces analytics on spreadsheets. Part 2 includes chapters 3 through 7. Part 3 covers chapters 8 through 12, and Part 4 covers decision analysis included in chapter 13. 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 System s Risk Solver Platform and XLMiner. Failure to pay attention to the organization and quality of your work file may reduce your overall grade. NO LATE ASSIGNMENT WILL BE ACCEPTED. It is your responsibility to submit the documents on or before the due date. Exams There will be three (3) exams. The exams are based on the three assignments and on 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. NO MAKEUP EXAMS will be given. Only the following reasons will be considered as grounds for a makeup exam if you miss an exam: armed services requirement, an extreme health situation, and death. Any exam 2

3 that is missed without an appropriate documentation will automatically receive a score of zero. Class Format, Policies, and Student Participation Attendance in 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 often 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 are 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, neatness, 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 and three exams. Letter grades will be assigned based on the following criteria as a percentage of total points: 92 and above: A 90 to less than 92: A- 87 to less than 90: B+ 82 to less than 87: B 80 to less than 82: B- 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 3

4 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 to make that determination. 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 Access the companion website to gain access to important course resources (data files) and download Frontline System add in to Excel Companion website at: 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. Class Schedule The Schedule (tentative) 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 Topic Description number and date 1 8/18 Chapter 1 & 2 Course overview 4

5 Introduction to Analytics and Excel Decision Models Problem Solving and Decision Making Excel Functions Spreadsheet Add-ins for Business Analytics Spreadsheet Modeling 2 8/25 Chapters 2 & 3 Introduction to Excel/Frontline Systems Exploring data Data Visualization Data Queries: Using Sorting and Filtering Statistical Methods for Summarizing Data Exploring Data Using PivotTables Case 1: Introduction to Performance Lawn Equipment (PLE) 3 9/1 Chapter 4 Chapter 5 4 9/8 Chapter 5 & Chapter 6 Exploring data Descriptive Statistics Populations and Samples Measures of Location, Dispersion and Shape Measures of Association Excel Descriptive Statistics Tool Outliers Probability and Data Modeling Probability and Data Modeling Random Sampling from Probability Distributions Data Modeling and Distribution Fitting Sampling and estimation Estimating Population Parameters Sampling Error Sampling Distributions 5

6 5 9/15 Chapter 7 Interval Estimates Confidence Intervals Using Confidence Intervals for Decision Making Statistical inference Hypothesis Testing One-Sample Hypothesis Tests Two-Sample Hypothesis Tests Chi-Square Test for Independence 6 9/22 Chapter 7 Statistical inference Chi-Square Test for Independence Case 1 due 9/24 Exam 1: 9/24 7 9/29 Chapter 9 Regression Analysis Simple Linear Regression Residual Analysis and Regression Assumptions Building Good Regression Models 8 10/6 Chapter 9 Regression Analysis Case 2: Introduction to Performance Lawn Equipment (PLE) Multiple Linear Regression Building Good Regression Models Regression with Categorical Independent Variables 9 10/13 Chapter 9 Forecasting Forecasting Techniques Qualitative and Judgmental Forecasting Statistical Forecasting Models Forecasting Models for Time Series with a Linear Trend 10 10/20 Chapter 10 Forecasting Forecasting Time Series with 6

7 Seasonality Selecting Appropriate Time-Series- Based Forecasting Methods Regression Forecasting with Causal Variables 11 10/27 Chapter 11 Case 2 due 10/27 Exam 2: 10/27 Simulation and Risk Analysis Simulation and Risk Analysis Spreadsheet Models with Random Variables Monte Carlo Simulation Using Risk Solver Case 3: Introduction to Performance Lawn Equipment (PLE) Last day to drop w/o academic penalty: 10/ /3 Chapter 11 & Chapter 12 Simulation and Risk Analysis Simulation and Risk Analysis Overbooking Model Introduction to data mining The Scope of Data Mining Data Exploration and Reduction 13 11/10 11/11 Chapter 12 Veterans Day No Classes Introduction to data mining Classification Classification Techniques Association Rule Mining 14 11/17 Chapter 12 & Chapter 13 Introduction to data mining Cause-and-Effect Modeling Decision Analysis Making Decisions with Uncertain Information Decision Trees 7

8 15 11/24 Chapter 13 Draft of case 3 for review Special problem in Decision making Thanksgiving holiday 11/26-11/ /1 Chapter 13 Decision Analysis The Value of Information Utility and Decision Making 17 12/8 Final exam week Case 3 due Exam 3 (final exam) Tuesday, December 9, 7:30 am 10:15 am You should not discuss your case analysis or share your work with any other person in the class. Eagle mail ( ) will be used for special announcements; CANVAS will be used only to post cases, articles and other course materials not in the course package. CANVAS is not used to post grades you must come to class to get your graded exams, cases, and other assignments. If you have questions about any of the material ask me in class, a question to me, or see me in my office. Please follow the university guidelines regarding academic dishonesty and plagiarism. Academic Behavior Standards and Academic Dishonesty All students are expected to demonstrate honesty in their academic pursuits. The university policies regarding issues of honesty can be found in the FGCU Student Guidebook under the Student Code of Conduct and Policies and Procedures sections. All students are expected to study this document which outlines their responsibilities and consequences for violations of the policy. The FGCU Student Guidebook is available online at Disability Accommodations Services 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 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 contact the Office of Adaptive Services. The Office of Adaptive Services is located in Howard Hall 137. The phone number is or TTY

9 Student Observance of Religious Holidays All students at Florida Gulf Coast University have a right to expect that the University will reasonably accommodate their religious observances, practices, and beliefs. Students, upon prior notification to their instructors, shall be excused from class or other scheduled academic activity to observe a religious holy day of their faith. Students shall be permitted a reasonable amount of time to make up the material or activities covered in their absence. Students shall not be penalized due to absence from class or other scheduled academic activity because of religious observances. Where practicable, major examinations, major assignments, and University ceremonies will not be scheduled on a major religious holy day. A student who is to be excused from class for a religious observance is not required to provide a second party certification of the reason for the absence. CANVAS Learning Management System and Demonstration Site Information on CANVAS is available online at the FGCU website. Library Resources Main page: Tutorials & Handouts: Research Guides: Contact: * This is a planned course structure and may change if necessary to meet learning goals 9

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