BUSW 352 Business Quantitative Methods Assessment Coursework | ERAU

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University Embry-Riddle Aeronautical University (ERAU)
Subject BUSW 352 Business Quantitative Methods

BUSW 352 Assessment Coursework

Instructor Information

Name Thomas Hiestand
Email hiestfdc@erau.edu

Required Course Materials

Title: Required reading materials are provided free of charge in your course.

Format: Note
Notes – A microphone and video camera are required to complete some assignments.

Course Information

Credit Hours: 3

Delivery Method: Online (Internet/Canvas)

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Catalog Course Description

Development, implementation, and utilization of business models for managerial decision making. Various techniques for modeling, such as statistical analyses techniques, data analysis, regression and correlation analysis, forecasting, simulation, and optimization models are covered. Developing models needed in decision support systems using Microsoft Excel.

BUSW 352 Prerequisite is STAT 211 or STAT 222.

Course Goals

The course is designed to provide the students with quantitative tools commonly used in business settings. This course familiarizes students with analyzing data and how to generate managerial reports for decision making using Microsoft Excel. This course enables the students to perform various managerial analyses including statistical modeling, financial analyses, mathematical and simulation analysis.

Student Learning Outcomes

  1. Apply the principles of quantitative methods to various business disciplines.
  2. Analyze large data sets in the context of business problems.
  3. Formulate and test hypotheses using collected data.
  4. Use variable analysis to make business decisions.
  5. Assess various business scenarios with computer-based mathematical models andfunctions within Microsoft Excel.
  6. Employ forecasting, regression, simulation, financial planning, budgeting, pricing,marketing, project management and optimization tools to multiple business scenarios.

Grading

Scale Grade
90 – 100 A (Superior)
80 – 89 B (Above Average)
70 – 79 C (Average)
60 – 69 D (Below Average)
0 – 59  F (Failure)

Disability and Special Needs and Mental Health Wellness

Disability Services Support

ERAU-WW is committed to the success of all students. It is a University policy to provide reasonable accommodations to students with disabilities, who qualify for services. If you would like to request accommodations due to a physical, mental or learning disability, please visit the Worldwide Student Accessibility Services page or contact our office at

386-226-7334 or via email at wwsas@erau.edu. ALL DISCUSSIONS ARE CONFIDENTIAL.

Mental Well-Being Statement

ERAU recognizes that life stressors, such as depression, anxiety, alcohol/drug problems, relationship problems and various other experiences can hinder the learning process. All ERAU students have access to free, confidential counseling through TELUS Health. You can access a counselor 24/7 via phone, computer or chat in the Student Support app. Please download the app or add the link to your computer and consider using this valuable resource during your educational journey at ERAU. More information on TELUS can be found on the WW Dean of Students ERNIE page.

Evaluation Items & Weights

Percentage

Data Assignments: 75%

Modules 1–8

Data Assignment: Module  15% 9

Virtual Study Groups    10%
                            100 Total %

Assignment Type

Data Assignments: Modules 1–8

You will complete data-focused assignments exploring challenges in the aviation industry, statistical analyses, visualization techniques, and predictive modeling. Tasks include data sourcing, cleaning, and creating visualizations in Excel, performing statistical tests, applying decision trees, and running Monte Carlo simulations. Emphasis is placed on deriving actionable insights and practical applications.

Data Assignment: Module 9

In this standalone assignment, you will develop a logistic regression model to predict tire failures, evaluate its performance using confusion matrices and ROC curves, and recommend maintenance strategies. This capstone-style task integrates advanced statistical modeling and data interpretation for real-world aviation challenges.

Virtual Study Groups

Collaborative virtual study groups are integrated into Modules 5, 7, and 9 to foster peer learning and discussion. You will explore complex concepts like statistical methods, decision trees, and logistic regression. Participation is graded on active engagement, meaningful contributions, and collaboration to enhance understanding and problem-solving skills.

Additional Information

Please note that you may be able to see the course content up to 4 (four) days prior to the official term start date. However, you will not be able to actively participate in the course (e.g., submit assignments, participate in discussions, receive credit for an activity, etc.) until 12am on the official day of term start.

APA Format

Go to the APA website for additional information about the American Psychological Association Publication Manual.

Library

Embry-Riddle Aeronautical University has one of the most complete library collections of aviation-related resources in the world. The Hunt Library is the library for all Worldwide students regardless of location. For help finding resources for your assignment, project, or topic, or to learn more about the library services available to you, please contact our librarians using the following information:

o Library Basic Training

o Ask-a-Librarian

o Library Hours

  • Contact Information

o Email: library@erau.edu

TITLE IX

The Title IX Office oversees compliance of Title IX Sexual Harassment in accordance with Federal Regulations, as well as incidents falling under the University Sexual Misconduct policy. Policy violations can include sex discrimination, sexual harassment, or sexual violence, such as rape, sexual assault, relationship / dating violence, sexual misconduct, and stalking.

Anyone may report suspected or known violations to the Title IX Office and may be able to receive supportive measures. Please see the Title IX website for additional information.

WW Title IX Office

Email: wwtitle9@erau.edu

Website: https://worldwide.erau.edu/administration/title-ix-compliance

Online Complaint Form

Course Policies

Academic Integrity

Embry-Riddle is committed to maintaining and upholding intellectual integrity. All students, faculty, and staff have obligations to prevent violations of academic integrity and take corrective action when they occur. The adjudication process will involve imposing sanctions which may include, but are not limited to, a failing grade on the assignment, a failing grade in a course, suspension, or dismissal from the University, upon students who commit the following academic violations:

  1. Plagiarism: Presenting the ideas, words, or products of another as one’s own. Plagiarism includes use of any source to complete academic assignments without proper acknowledgment of the source. Reuse or resubmission of a student’s own coursework if previously used or submitted in another course, is considered selfplagiarism, and is also not allowed under University policy.
  2. Cheating: A broad term that includes, but is not limited to, the following:
    1. Giving or receiving help from unauthorized persons or materials during examinations.
    2. The unauthorized communication of examination questions prior to, during, or following administration of the examination.
    3. Collaboration on examinations or assignments expected to be, or presented as, individual work.
    4. Fraud and deceit, that include knowingly furnishing false or misleading information or failing to furnish appropriate information when requested, such as when applying for admission to the University.

Note: The Instructor reserves the right to use any form of digital method for checking plagiarism. Several electronic systems are available and other methods may be used at the Instructor’s discretion.

Online Learning

This course is offered through Embry-Riddle Online (Canvas) and runs nine (9) weeks. The first week begins the first day of the term and ends at midnight EDT/EST (as applicable) seven days later. Please note that all assignments, unless otherwise indicated, are due by 11:59p.m. EDT/EST on the date shown. Success in this course requires in-depth study of each module as assigned, timely completion of assignments, and regular participation in forum discussions.

Late work should be the exception and not the rule and may be downgraded at the discretion of the Instructor, if accepted at all. Unless all work is submitted, the student could receive a failing grade for the course. Extensions may be granted for extenuating circumstances at the discretion of the Instructor and only for the length of time the Instructor deems appropriate. The most important element of success in an online course is to communicate with your Instructor throughout the term.

Conventions of “online etiquette,” which include courtesy to all users, will be observed. Students should use the Send Message function in Canvas for private messages to the Instructor and other students. The class discussion forums are for public messages.

It is highly recommended that students keep electronic copies of all materials submitted as assignments, discussion posts and emails, until after the end of the term and a final grade is received. When posting responses in a discussion forum, please confirm that the responses have actually been posted after you submit them.

Summary

  • Before you begin the course, read the Important Course Information and other items in the Start Here module. If you have any questions, please contact your instructor.
  • Visit the Modules area for an overview of the course structure and direct navigation to all course content.
  • All assignments due by 11:59 pm ET.
1.1 Discussion: Introductions Discussion 0
Online Office Discussion 0
Student Lounge Discussion 0
8/17/25 1.3 Data Assignment: Aviation Industry Challenges Assignment 100
8/24/25 2.2 Data Assignment: Visualization Portfolio Assignment 100
8/31/25 3.2 Data Assignment: Applying Statistical Distributions to Aviation Data Analysis Assignment 100
9/7/25 4.2 Data Assignment: Confidence Intervals and Hypothesis Testing in Excel Assignment 100
9/14/25 5.2 Data Assignment: Statistical Analysis of Aviation Data Assignment 100
9/14/25 5.3 Discussion: Virtual Study Group Discussion 100
9/21/25 6.2 Data Assignment: Regression Analysis Assignment 100
9/28/25 7.2 Data Assignment: Decision Tree Assignment 100
9/28/25 7.3 Discussion: Virtual Study Group Discussion 100
10/5/25 8.2 Data Assignment: Applying Monte Carlo Simulations Assignment 100
10/12/25 9.2 Data Assignment: Tire Failure Prediction and Maintenance Optimization Assignment 100
10/12/25 9.3 Discussion: Virtual Study Group Discussion 100

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