Intro and Syllabus

Course Overview

  • Welcome to COB 191: Business Analytics

    • Instructor: Jaja (Assistant Professor in Computer Information Systems and Business Analytics)

    • Importance of using English effectively, as it is the instructor's second language.

    • Open invitation for feedback on explanations and clarity.

Course Structure

  • Canvas as the primary platform for course materials and updates.

    • Students encouraged to log into the Canvas page to access resources.

AI Teaching Assistant (TA)

  • Introduction of AI-based virtual TA available for the course.

    • Designed to help students with quick queries before reaching out to the instructor.

    • Covers course policies, assignment details, and other essential information.

    • Students to consult with AI TA for immediate questions before contacting the instructor for complex issues.

Syllabus Overview

  • Syllabus available on Canvas homepage or via syllabus navigation.

    • Includes details on course structure, policies, and grading criteria.

Instructor Background

  • Instructor's experience: 4 semesters at JMU, previously at University of Texas Permian Basin.

    • Introduction of personal anecdotes to establish rapport with students.

Understanding of Business Analytics

  • Discussion on the meaning of Business Analytics:

    • Collecting and analyzing various types of data to inform business decisions.

    • Examples of real-world applications like purchasing decisions.

    • Key Elements: Data analysis, decision making, future predictions.

Classroom Dynamics

  • Instructor encourages student interaction:

    • Students asked about academic majors to tailor examples and discussions.

    • Engagement through questions and feedback is prioritized in the class.

Course Expectations and Success Factors

  • Emphasis on active participation, note-taking, and collaboration.

    • Students are encouraged to discuss course content with peers and assist each other.

  • Importance of self-scheduling study and review sessions to ensure comprehension of materials.

Learning Objectives

  • Detailed learning objectives will be available on Canvas.

  • Importance of aligning material learned in class with these objectives.

Recommended Textbooks

  • Two textbooks recommended for course support:

    1. Modern Business Statistics with Microsoft Excel.

    2. Additional textbook developed by former professor Scott Stevens.

Course Assignments and Assessment

  • Major components of grading:

    • Two Excel assignments (12.5% of total grade)

    • Ten after-class quizzes (12.5% of total grade)

    • Three tests (50% of total grade)

    • Final exam (25% of total grade)

Assignments Guidelines

  • Timely submission required, late submissions not accepted without prior arrangement.

    • Students must request extensions at least 48 hours in advance.

    • No pre-grading or review of assignments before submission.

Quizzes

  • Conducted after each chapter to reinforce learning.

    • Unlimited time and up to three attempts allowed; the highest score will count towards the final grade.

Exams

  • Three non-cumulative tests and one cumulative final exam.

  • Closed-book testing environment with one double-sided T-sheet allowed.

    • Standardized calculators permitted.

  • Policy on missed tests: If missed, the score will count as 80% of the lowest of the other two tests.

Attendance and Participation Policy

  • Regular attendance and active participation encouraged but not strictly monitored.

  • Possibility for extra credit through participation and engagement in discussions.

Instructor Expectations

  • Instructor aims for students to succeed and clarify doubts actively.

  • Assignments and tests must be submitted on time.

  • Open communication encouraged regarding academic struggles or questions.

Withdrawal and Accommodations Policy

  • Last date for free withdrawal: February 10.

  • Students needing extra time or accommodations must contact the Office of Disability Services.

Course Schedule

  • Detailed course schedule provided to outline weekly topics and assignments.

  • Regular updates will be communicated through Canvas announcements to adjust for scheduling changes or student needs.

Utilizing AI Tools

  • Encouragement to leverage AI tools for learning business analytics concepts effectively.

  • Awareness that careful questioning is necessary to receive accurate data from AI models.