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MATH-104-SF1 Quantitative Fluency for Business Managers and Leaders

Course Description

The course focuses on developing competency in quantitative fluency and analytical skills through the application of quantitative theories, tools, and models to empirically grounded and data-driven projects and scenarios in business. Topics include formulating and presenting quantitative information in professional settings, inferential, statistical analysis, analysis of data related to quality control and quality management, data-driven decision-making in contexts of uncertainty, and financial decision-making. An aim of this course is to help students develop a general competency in the use of quantitative methods, knowledge, and reasoning skills essential for decision-making in business. Prerequisite(s): MATH 40.

Course Learning Outcomes

After successfully completing this course, students can expect to be able to:

● Explain the value of mathematical reasoning and analysis for maximizing both managerial and personal resources.

● Compare the merits and limitations of commonly used quantitative techniques

● Build simple linear, multiple, quadratic regression models and interpret regression analyses

● Construct time series forecasting models

● Articulate quantitative results in written and graphic formats.

● Evaluate a business situation to identify a quantifiable problem, distinguish relative issues, and develop an action plan for a solution.

● Employ quantitative and inferential analyses that support sound decision making.

Course Materials

Textbook(s)

● Modern Business Statistics with Microsoft® Excel® by Anderson et al. ISBN: 9780357708620 (You may use a physical paper copy or online version of the text.)

Software:

● Microsoft Excel for PC or MAC: https://www.microsoft.com/en-us/education/products/office Also, see the resources available to you at the myGGU Portal.

Calculator:

● Optional scientific or graphing calculator

Other Required Materials

None

Bookstore

You may purchase course materials from GGU's official online bookstore: https://www.bkstr.com/goldengatestore/home/en

Classroom Guidelines & Student Responsibilities

Students have the following responsibilities in this, and any other course taught at Golden Gate University:

1) Review the Classroom Guidelines and Student Responsibilities policies below that apply to all courses.

2) Read syllabus and course information carefully.

3) Read lectures and other required learning materials online carefully.

4) Participate in discussions (in-person and/or online) and engage in learning activities.

5) Actively engage the material and ask questions of the instructor when confused about any aspect of the course.

6) Complete activities (discussion, quizzes, case studies, essay, applied learning assignment and final exam) in a timely manner following the instructions for each activity.

7) Treat other students and the instructor with civility and respect.

8) Abide by the Student Code of Conduct

9) For courses that contain a web conference (Zoom) component: enable your webcam so that your face is visible to instructors and classmates in synchronous web conference classes. This promotes full engagement and a sense of community. If you have concerns about privacy, please use a virtual background that hides your physical background or consult with your instructor.

Course Requirements

You will have reading assignments, homework assignments, a midterm, a final exam, and a project. You will be assigned reading from the text for each session. I also recommend that you read through the exercises for each section. Paying attention to the case problems at the end of each chapter, whether assigned or not, will give you some ideas for your project, prepare you for each exam, and give you a better understanding of what you are learning. There will be 12 homework assignments. Each assignment will be due at the start of the class session or as indicated on the course website. The homework must be submitted online by following the submission link on the course page. Late homework will not be accepted (unless a pre-class arrangement has been made with the instructor). The mid-term (take-home) exam and the final exam will each be worth 20% of your grade. In addition, the final exam will be a 2:40 hours long on-line (eLearning) exam. While the use of course materials is allowed during the exam, you must work on the exam independently. Further details regarding the exam will be provided during the course. The final project is your opportunity to apply what you are learning to collect and analyze data that is of interest to you. This is the signature assignment. Therefore, it is encouraged that you begin this project early in the semester and that you will add to as you learn new concepts and techniques. The project will culminate in a written report. It can be done independently or in small groups of up to 4 students. Teamwork and collaboration on the project are encouraged.

Participation and Attendance

Due to the ongoing pandemic, we will hold our live lectures via Zoom (start at 6:50PM every Thursday). For successful completion of the course, it is important for you to participate in each class session. Questions and comments are welcome at any time throughout the class session. Full participation is expected for all in-class sessions, including the first week. Success in this course require full engagement and participation. If you have to miss a class, please notify the instructor of the course as soon as possible via email and be sure to go over the material on your own.

Grading Policy

The weight of each graded activity in this course is shown below.

Policies and Resources

Click here to review policies for this course: https://www.ggu.edu/undergraduate/policies-and-resources/

These policies and resources are part of this course syllabus. The following policies, available at the link above, apply to all courses:

● Resources such as:

○ Bookstore

○ Business Library

○ Tutoring

○ Disability Resources for Students

○ Wellness Resources for Students

● Policy on Academic Integrity

● GGU Grading Policy

● Instructional Methods and Related Policies

Instructor Bio

Vera Klimkovsky is an Adjunct Professor of Management in the School of Business and the School of Undergraduate Studies at Golden Gate University. She brings in 20 years of teaching Statistics, Business Analytics, and Mathematics. Vera has taught levels 1 and 2 of the quantitative portions of the Chartered Financial Analyst exam preparation workshop at GGU. Vera holds a B.S. in Applied Mathematics and an M.A. in Mathematics. She has also undergone training at UC Berkeley, Department of Public Health, and her research focused on simulation studies and implementation of multiple hypothesis testing procedures. As the Chair of Marketing and Publicity at the Association for Computing Machinery, SF Bay ACM local chapter, Vera took part to organize the annual Data Science conferences and Data Science Special Interest Group (DSSIG) meetings. Her goal as a professor at Golden Gate University is to share her passion for Applied Statistics and Data Science to help students stay current in the field and successfully apply the knowledge and skills they acquire in class in the workplace.