BUS 210 Master Syllabus

BUS 210: Business Analytics I

Course Instructor:
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Required Course Materials:

Business Analytics, Methods, Models, and Decisions, 3rd Ed., by James R. Evans, Pearson Higher Education, 2020, ISBN-13: 978-0-13-523167-8
Book Rental, Pearson +
ISBN with Mylab: 9780135834893
- This will also be the textbook for BUS 310 in the following semester.
- A current textbook is required for the course, new, used, ebook, or rental.
- Example files you are required to download for class

Course Website:

Course Description

This course introduces students to solving a broad set of data analysis problems using the Python programming language. The course will cover Python programming fundamentals such as variables, object types, loops, conditional statements, and functions. The course will also help students learn to use a series of Python library and packages for business analytics that involve data manipulation, descriptive analysis, and data visualization. Finally, the course will introduce students to basic machine learning techniques such as prediction models.

BS Business Learning Goals

The social, global, ethical, and legal contexts of business and will be able to reflect on the role of the individual in business.
The ability to apply knowledge of professional skills necessary for success in business including effective business writing.
Technical and analytic skills appropriate for success in business.
The ability to apply knowledge of core business disciplines including accounting, finance, information systems, management, marketing, and operations management.
How research in the business disciplines contributes to knowledge and how such research is conducted.

Learning Outcomes

Upon completing this Quantitative Reasoning course, students will be able to:

Interpret quantitative information (i.e., formulas, graphs, tables, models, and schematics) and draw inferences from them.
Formulate a given problem quantitatively and use appropriate arithmetical, algebraic, and/or statistical methods to solve the problem.
Evaluate logical arguments using quantitative reasoning.
Communicate and present quantitative results effectively.

Sequence Course Objectives for both BUS 210 and BUS 310

Understand how managers use business analytics to formulate and solve business problems
Prepare to be a strategic business partner in an organization
Think critically about whether and how data can improve business performance, create opportunities, and/or create risks

Additional Specific Course Objectives for BUS 210

Understand the processes needed to develop, obtain, and report business data
Use the science of probability and uncertainty to make business decisions
Gain a foundation of data analytics skills using technology and Excel

Course Topics

Introduction to Business Analytics and Data
1. Descriptive, Predictive, and Prescriptive Analytics
2. Data types
3. Data presentation
4. Data summarization
5. Getting the Right Data
Probability, Uncertainty, and Decision Making
1. Probability
2. Discrete random variables
3. Continuous random variables
Visualization of Data and Descriptive Analytics using Excel
1. Business spreadsheets
2. Graphing and visualizing data
3. Functions
  1. Relative and absolute references
  2. Using formulas involving arithmetic operators +, -, *, and /
  3. Using parentheses and percentage calculations
  4. Numbering formats, e.g., currency, accounting, comma, percent, etc.
  5. Copy formulas and filling neighboring ranges with data and data series
  6. Testing conditions (involving =, <, >, <=, >=, AND, OR, etc.)
  7. “IF” statements
  8. Using financial functions
4. Working with data in tables
  1. Sorting, filtering etc.
  2. Grouping/separating data in a table, generating subtotals, creating summaries
  3. Designing, building, using, and adding to/modifying PivotTables
5. Business modeling
  1. What-If Analysis using Goal Seek and Data Tables
  2. Pivot Table and Pivot Chart for the data analysis
  3. Excel Table for filtering data

Approach to Learning

This course examines the use of business analytics for understanding and analyzing business problems and for supporting business decision-making. It is geared for the business professional engaged in decision making or decision support. The emphasis is on business applications, and not mathematics. Students will possess an adequate level of proficiency in and comfort with spreadsheet software. The format will be lectures and hands-on exposure to data analytics tools, including complex Excel options. Discussions and questions are highly encouraged.

Computer/Software/Email

Access to the internet and a computer is required. Many of the course material will be online in our Blackboard course.

Students must use their Mason email account to receive important University information, including communications related to this class. I will not respond to messages sent from or send messages to a non-George Mason email address.

In correspondence/communication students will be required to:

Be professional and respectful in correspondence
Use proper email etiquette, including an introduction, your name, course and section information.
Make reasonable requests of the instructor. I will be happy to clarify course material and answer legitimate questions; however, please exhaust other information sources (e.g., syllabus, Canvas) for answering your question before contacting me and remember, “Poor planning on your part does not constitute an emergency on my part.”

Students who e-mail me Monday - Thursday can ordinarily expect a response within 24 hours. Students who e-mail after 4 PM on Friday or over the weekend can ordinarily expect a response by noon on the following Monday. Proper email completion allows for quick email responses.

You are required to bring a laptop to class with MS Excel.
The PC version of Microsoft Excel is required for the course. The latest version of Microsoft Excel is available for download for GMU students through your MasonLive account. It is the student’s responsibility to make sure the laptop to meet the required standards. Use of other operating systems, are at your own risk, and are discouraged. Refer to the College of Business Minimum Computing Requirements.

Methods of Student Evaluation

Students are evaluated based on homework, quizzes, case studies, exams, and class activities.

Grading

Homework assignments, Case studies, Quizzes, Class Work, Participation	40%
Exam 1	20%
Exam 2	20%
Final Exam	20%

Course Grade

Students must be officially registered in this section to receive a grade. It is the sole responsibility of the student to verify their own registration status. Specifically, you will not receive a grade if your name does not appear on the official class list. Registration problems should be directed to either the College of Business Academic Advisors or the Registrar’s Office.
Disputes about a grade on assignments/exams/quizzes must be submitted in writing within a week after the grade has been posted.
The final letter grade is assigned objectively and strictly according to the WEIGHTED average of the numerical scores of all exams, quizzes, and assignments.
Final course letter grade assignments:

Course Average (%)	Course Grade	Course Average (%)	Course Grade
97.00 to 100	A+	80.00 to 82.99	B-
93.00 to 96.99	A	77.00 to 79.99	C+
90.00 to 92.99	A-	70.00 to 76.99	C
87.00 to 89.99	B+	60.00 to 69.99	D
83.00 to 86.99	B	0 to 59.99	F

To promote fairness to all students, final scores are non-negotiable and will not be rounded up.

Compliance with the University’s Honor Code

George Mason University Honor Code: To promote a stronger sense of mutual responsibility, respect, trust, and fairness among all members of the George Mason University community and with the desire for greater academic and personal achievement, we, the student members of the University Community have set forth this: Student members of the George Mason University community pledge not to cheat, plagiarize, steal, and/or lie in matters related to academic work.

When turning in ANY assignment, you cannot copy another student's response or submit somebody else's work as your own. You are encouraged to work together through the discussion board forums. However, make sure all responses are written in your own words and that every file submitted is your own file created by you. George Mason University takes violations of the Honor Code seriously. You should take a moment to look at the last two pages of the syllabus to see the College of Business' sanctions for violations. Options for a "slap on the wrist" or a "warning" do not exist. The sanctions for a first offense are very serious for all class submissions. By choosing to take this course, you agree to uphold the George Mason University Academics Standard Code. Please note that faculty are obligated, without exception, to submit any Honor Code violations or suspected violations to the Honor Committee. In your work on all written assignments, keep in mind that you may not present as your own the words, work, or the opinions of someone else without proper acknowledgement.

Assignments Descriptions

Exams
Exam dates are provided in the schedule. No make-up exams will be given. Each exam will involve a mix of mechanical skills and conceptual reasoning. The best possible preparation is regular attendance and completion of assigned homework and reading.

Homework, Quizzes & Class Work
All Homework assignments will be due Sunday 11:59pm to Canvas of the relevant class week. Students are expected to read relevant sections of the textbook prior to attending class. Written homework, quizzes, and class work will be graded. Additional due dates will be given in class and will be posted on Canvas. Late assignments cannot be accepted. Quizzes and class work are given at the discretion of the instructor and frequently reflect material that has recently been discussed in class. To encourage attendance, instructors will not give makeup quizzes or class work.

Case Studies
At the end of each module, there is a case study pertaining to the topics discussed in that module.

Chapter 1: Performance Lawn Equipment
Chapter 2: People’s Choice Bank
Chapter 3: Performance Lawn Equipment
Chapter 4: Performance Lawn Equipment
Chapter 5: Performance Lawn Equipment

You are required to read the case description, follow the instructions provided on Canvas and answer the questions. A summary of your analysis, findings and recommendations will also be required.

To receive a grade, you must upload the Excel spreadsheet that shows your work as well as a word document showing a summary report of your findings. The word document should be written in a professional manner.

Attendance / On Time Arrival

Class attendance is essential part of learning for this course. On Time Arrival is required for this course. If you have to miss any lectures, you are responsible for obtaining any information given in the class.

Cell phones must be turned off during class. Note: Disruptive behavior will not be tolerated.

Discussion Boards / Participation Grade

For every discussion board, you are required to make your initial post addressing the challenges or questions in the module by 11:59 PM on Wednesday and reply to at least one classmate by 11:59 PM on Sunday. Your participation will be graded based on the quality of your initial post (relevant to the content, reference to reading materials, proper grammar) and replies to your classmates.

If you need help from the instructor, utilize the “Ask your instructor” discussion forum. Your engagement in the classroom will also count towards your participation grade.

Disability

All academic accommodations due to disability must be arranged through the Office of Disability Services (ODS). If you are a student with a disability and you require academic accommodations, please contact ODS at (703) 993-2474.

Working in Excel might be a challenge for blind students, so additional accommodations will be needed for this course. Please reach out the Office of Disability Services and the instructor right away as you might need a partner to work on the homework assignments and special exam accommodations.

Academic Integrity

The integrity of the University community is affected by the individual choices made by each of us. Mason has an Honor Code with clear guidelines regarding academic integrity. Three fundamental and rather simple principles to follow at all times are that: (1) all work submitted be your own; (2) when using the work or ideas of others, including fellow students, give full credit through accurate citations; and (3) if you are uncertain about the ground rules on a particular assignment, ask for clarification. No grade is important enough to justify academic misconduct.

Costello College of Business Standards of Behavior

The mission of the Costello College of Business at George Mason University is to create and deliver high-quality educational programs and research. Students, faculty, staff, and alumni who participate in these educational programs contribute to the well-being of society. Highquality educational programs require an environment of trust and mutual respect, free expression and inquiry, and a commitment to truth, excellence, and lifelong learning. Students, program participants, faculty, staff, and alumni accept these principles when they join the Costello College of Business community. In doing so, they agree to abide by the following standards of behavior:

Respect for the rights, differences, and dignity of others
Honesty and integrity in dealing with all members of the community
Accountability for personal behavior

Integrity is an essential ingredient of a successful learning community. Ethical standards of behavior help promote a safe and productive community environment, and ensure every member the opportunity to pursue excellence. The Costello College of Business can and should be a living model of these behavioral standards. To this end, community members have a personal responsibility to integrate these standards into every aspect of their experience at the Costello College of Business. Through our personal commitment to these Community Standards of Behavior, we can create an environment in which all can achieve their full potential.

Diversity

The College of Business, an intentionally inclusive community, promotes and maintains an equitable and just work and learning environment. We welcome and value individuals and their differences including race, economic status, gender expression and identity, sex, sexual orientation, ethnicity, national origin, first language, religion, age, and disability.

Anti-Racism

As a member of the George Mason University community, the College of Business plays an integral role in building an educational environment that is committed to anti-racism and inclusive excellence. An anti-racist approach to higher education acknowledges the ways that individual, interpersonal, institutional, and structural manifestations of racism against Black individuals and other people of color contribute to inequality and injustice in our classrooms, on our campuses, and in our communities, and it strives to provide our community members with resources to interrupt cycles of racism so as to cultivate a more equitable, inclusive, and just environment for all of our students, staff, faculty, alumni, and friends, regardless of racial background.

To be anti-racist means:

To make constant, conscious decisions to interrupt racism and cultivate equity, inclusion, and justice for people of all racial backgrounds, and in particular those from Black communities and other communities of color, who are most likely to bear the direct and indirect costs of systems of white supremacy;
To interrogate histories of white supremacy and white-dominant culture, and to examine the ways in which these histories have impacted our individual beliefs, our interpersonal relationships, our institutional and structural policies and processes, and our entire society;
To make a commitment to being responsible for our own relationships to, and actions within, systems of white supremacy; and
To cultivate a practice of self-awareness and self-reflection that allows us to critically evaluate our own role in upholding white supremacy and identify the ways we can interrupt cycles of racism at the individual, interpersonal, institutional, and structural levels.

We believe that the work of anti-racism starts with each individual, and that in cultivating an anti-racist approach to research, scholarship, and practice, our students will build a skillset rooted in principles of equity, inclusion, and justice that they will carry with them throughout their lives.

Gender Identity and Pronoun Use

If you wish, please share your name and gender pronouns with me and how best to address you via email.

Campus Closure

If the campus closes or class is canceled due to weather or other concern, students should check Canvas for updates on how to continue learning and information about any changes to events or assignments.

Tentative Course Schedule: Fall

Expect to work 7-10 hours per week on assignments for this course. Unless otherwise stated, all assignments are due by the end of the week in which they are assigned. For the purposes of this course, a week is defined as beginning at 12:01 am each Monday EST, and ending at 11:59 pm on the following Sunday EST.

If you have a question or concern or encounter a problem about an assignment, please contact me immediately so we can discuss and work out a resolution.

This schedule may change. Revisions will be posted on Canvas.

Weeks	Learning Modules	Assignments
Week 1 Aug. 26-Sep. 1	Chapter 1: Introduction to Business Analytics
Week 2 Sep. 2-8	Labor Day: Sept. 2 Chapter 2: Database Analytics
Week 3 Sep. 9-15	Chapter 2 cont.
Week 4 Sep. 16-22	Chapter 2 cont.
Week 5 Sep. 23-29	Chapter 3: Visualization
Week 6 Sep. 30-Oct. 6	Chapter 3 cont.	Midterm 1
Week 7 Oct. 7-13	Chapter 4: Descriptive Statistics
Week 8 Oct. 14-20	Fall Break: Oct.14 Chapter 4 cont.
Week 9 Oct. 21-27	Chapter 4 cont.
Week 10 Oct. 28-Nov. 3	Chapter 4 cont.	Midterm 2
Week 11 Nov. 4-10	Chapter 5: Probability and Probability Distributions
Week 12 Nov. 11-17	Chapter 5 cont.
Week 13 Nov. 18-24	Chapter 5 cont.
Week 14 Nov. 25-Dec. 1	Chapter 5 cont. Thanksgiving Recess: Nov. 27-Dec. 1
Week 15 Dec. 2-8	Chapter 5 cont.
Week 16 Dec. 9	Chapter 5 cont. / Review
Dec. 10 Exam Week Dec. 11-18	Reading Day See Final Exam Schedule	Final Exam

Academic Standards Code

Academic Standards exist to promote authentic scholarship, support the institution’s goal of maintaining high standards of academic excellence, and encourage continued ethical behavior of faculty and students to cultivate an educational community which values integrity and produces graduates who carry this commitment forward into professional practice.

Violations and Sanctions

Violations

Unauthorized Assistance
Unauthorized assistance means using, accessing, or providing assistance to others when such assistance is not permitted per the university, course, or assignment instructions/policy. Unauthorized assistance also includes submitting academic work that was created, in whole or part, using unauthorized material. Certain departments may include requirements that go beyond what is mentioned, including a prohibition of sharing work, and the requirement to keep work secure. Examples of unauthorized assistance include but are not limited to:

Benefitting or attempting to benefit from unauthorized assistance
Providing unauthorized assistance
Unauthorized use of artificial intelligence software, generative or otherwise
Submitting work that was done, in part or whole, by someone else
Compensating someone else to do work and/or academic outsourcing
Making an unauthorized record of (photo, screenshot, download) and/or posting (such as on a public website or in group messenger apps) exams or academic content
Submitting work as one’s own that was obtained from unauthorized websites (including Quizlet, Chegg, Course Hero, etc.)

Fabrication
Fabrication in an academic context refers to providing information known to be false to bypass classroom expectations or gain an unfair advantage in completing academic work. Examples of fabrication include but are not limited to:

Providing a false excuse for missing a test, assignment, or class
Fabricating or providing false sources, data, information, documents, and/or official correspondence. This may include, but is not limited to, referencing material that does not appear in the indicated source
Providing false or altered documents in response to an Academic Standards violation

Plagiarism
Plagiarism in an academic context refers to using other individuals’ ideas or words without appropriate attribution or credit. It also includes reusing one’s own work that has already been submitted for a class or published without permission from the current instructor and/or without proper citation. Examples of plagiarism include but are not limited to:

Submitting another’s work as your own, either in whole or in part
Misrepresenting authorship (may include leaving author names off a document or giving authorship credit that is not warranted)
Failure to attempt to cite sources using required citation standards, including both intext/in-presentation citations and full references lists
Intentionally or unintentionally using portions of one’s old work for new assignments without advanced permission from the current course instructor and appropriate attribution. (self-plagiarism)

Plagiarism does not include mistakes in the format of a citation if the student has indicated the materials quoted or relied upon and the source of the materials.

Sanctions

George Mason has developed an institutional sanctioning matrix that assigns grade-related sanctions, educational sanctions, and potential institutional separation depending on the violation level. The sanctioning matrix is the definitive document outlining what sanctions, including grade sanctions, will result if a student is found in violation of the institution’s Academic Standards and should not be deviated from.

Please note a failing grade or an inability to continue as a student of George Mason University due to a grade-related sanction is not considered a punitive measure. Students are encouraged to consider potential outcomes of Academic Standards violations when submitting academic work.

The sanctioning matrix can be found on Canvas.

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