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 OMGT 6123 - Fall 2026, Sections 601 and 602

Quantitative Methods
Online Sections

Class Materials / Grading / About the Instructor / Course Outline / Home

Instructor: Dr. John F. Kros

Phone:  328-6364

Office:  3205 Bate Building

Email: krosj@ecu.edu

Office Hours: 12:30 pm - 2:15 pm TWTh or by Appointment

Webpage: http://myweb.ecu.edu/krosj/ecu.html


Watch the Syllabus Narrative (available after I turn on the course in Canvas)

Text:

Spreadsheet Text Cover

Custom Text for Quantitative Methods, Kros, Kendall/Hunt

Order the eBook of the text directly from KendallHunt: https://he.kendallhunt.com/product/custom-spreadsheet-modeling-business-decisions

or obtain from ECU Bookstore, UBE, etc.



NOTE: Joyner Library has hard copies of the full spreadsheet textbook (i.e., the textbook that the custom text was created from) available for student use on a reference and first come first served basis.  If available it is absolutely acceptable to use the full text as reference. 

Text Website: Website for Custom Text for Quantitative Methods. Contains Excel Templates, STUDY GUIDE, interactive models, etc. You need to use the code that accompanies the textbook to access the site. If you procure a used hard copy text you will not have access to the Online Text Materials.

Course Description and Goals:

Catalog Description - Basic quantitative concepts and their applications to decision models (Prerequisite:  Admission to MBA program).

This course engages diverse opinions & scholarly perspectives to develop critical thinking, analysis, & discussion as well as these tenets:

Think Critically
     Apply the DECIDE framework to develop an understanding of quantitative methods.  Terminology and quantitative models are introduced.

Value
     Utilize the EDGE perspective to survey basic quantitative methods and their application to business.

Communicate
     Compose written analysis that defend recommendations and solutions within the context of quantitative methods.

Lead
     Demonstrate effective leadership skills to successfully structure and complete collaborative/interactive work.
Laptop/Computer Requirement:  The College of Business requires that all students enrolled in a College of Business course acquire and have available a laptop or computer for use in and out of the classroom environment. The laptop or computer must be capable of running Microsoft Windows and the latest version of Microsoft Office. Faculty may also require other specialized software applications. Additional information may be found at https://business.ecu.edu/technology/

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Assignments:

Homework - 5 @ 5% .................................................................................................25.0%

Quizzes 5 @ 14% per.................................................................................................70.0%

Final Exam - Opens 5 pm, Dec 2nd & closes11:59 (midnight) pm, Dec 7th...............5.0%

ALL ASSIGNMENTS THAT ARE NOT AUTO-GRADED VIA CANVAS (E.G., FINAL EXAM OR QUIZZES) ARE EXPECTED TO BE SUBMITTED VIA CANVAS USING FILE ATTACHMENTS. PLEASE MAKE YOURSELVES FAMILIAR WITH USING PROGRAMS SUCH AS: MS Word (.doc files), Adobe Acrobat (.pdf files), and any commercial screen shot software (i.e., Snapz Pro, Screencatcher, etc.). THIS IS A MUST FOR THIS CLASS, CONTACT THE INSTRUCTOR IF YOU DO NOT UNDERSTAND THIS POLICY OR NEED ASSISTANCE.

FILE NAMING CONVENTION FOR SUBMITTING ASSIGNMENTS TO CANVAS:

PLEASE USE THE FOLLOWING NAMING CONVENTION WHEN SAVING AND SUBMITTING COMPLETED ASSIGNMENT FILES:

lastnamefirstinitialassignment.suffix

For example, for myself I would name my first homework assignment file:

krosjhomework#1.doc

Be forewarned, I will either send your assignments back to you ungraded or downgrade your work if you do not follow this naming convention.

Grading:

Homework problems are required to be completed and will make up the 25% of the course grade allocated above.  There may be a paired portion of the homework and an individual portion of the homework on some homework assignments.  Unless the homework specifically states there is a paired portion of the assignment you can assume there is none.  Homework can not be made up.

The quizzes will cover material from the text and my lectures. The problems on the quizzes will be similar to the homework problems. Missed quizzes will receive a zero grade. Please make prior arrangements if a quiz will be missed.

Final grades will be assigned by letter and will be derived approximately from the grading percentages shown above roughly following the standard four point A, B, C, F scale.  Roughly the following grade cut-offs will be used: 3.51 and above = A, 2.7 up to 3.51 = B, 1.7 up to 2.7 = C,  below 1.7 = F.

Percentage scores will not be assigned.  I will assign grades on individual assignments according to a +/- scale (A = 4.0, A-=3.7, B+=3.3, B = 3.0, B-=2.7, C+=2.3, C = 2.0, C-=1.7, F = 0.0).  Percentage scores WILL NOT be assigned.

COB PROCTOR POLICY
While I am including the following info, F2F proctoring is not required for this semester.  I will not be requiring proctored assignments for this semester.

Many of the online courses you enroll in may require a proctor.  A proctor is someone who is approved to administer examinations or other course material on behalf of the course instructor.  The purpose of the proctor is to assure the integrity of the examination process.  The university academic integrity policy may be reviewed at http://www.ecu.edu/studenthandbook/III.htm.

Attendance: I will not be taking attendance, but I will be posting and updating video tutorials throughout the semester.  It would behoove everyone to view those video tutorials.

Continuity of Instruction:  In the event that classes are suspended due to a pandemic or other catastrophe I will strive to continue instruction to those that are able to participate.  If and when classes are suspended, you will receive an email from me and an announcement that detail how we will communicate, where you can locate course information and what you can expect during this time period.  I will continue to provide instruction to those that are able to continue.

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Academic Integrity: Any academic dishonesty will result in a failing grade and appropriate university disciplinary actions taken. Please do your own work. If you do not understand the academic integrity policy of the ECU Marketing and Supply Chain Management Department please see the instructor.

Suggestions: To do well in this class the following hints might help.

1. Do the homework - correct or incorrect, I will do my best to reward your effort if possible.

2. Work with others - feel free to discuss problems and methodology on homeworks*.

3. Ask the instructor for help.  If you do not understand or are confused about an assignment or feedback I give, call, email, or stop by to discuss those issues, early and often as needed.

 * Quizzes are individual assignments and are expected to be completed without collaboration or discussion with any other student.

About the Instructor: John F. Kros has a bachelors degree in business from The University of Texas, an MBA from Santa Clara University, and a Ph.D. in Systems Engineering from The University of Virginia. He spends his free time traveling, snow skiing, watching college football, and trying to locate establishments that sell cheap liquid refreshment.

East Carolina University seeks to comply fully with the Americans with Disabilities Act (ADA). Students requesting accommodations based on a disability must be registered with the Department for Disability Support Services located in Mendenhall, Suite 109, (252) 737-1016 (Voice/TTY).

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Tentative Schedule:

TAKE NOTE: Bold Items Indicate Dates When Assignments are Posted or When they are DUE

(e.g., 8/24 is in bold yellow as it is the due date for HW 1)


Date


Notes - .ppt's


Handouts, etc.

Chapter in Textbook

Aug 17


Quantitative Methods Overview

Quantitative Methods Overview Video - Lecture

1

18

Descriptive & Numerical Statistics I

Descriptive & Numerical Statistics I - Lecture

3

19

Descriptive & Numerical Statistics II


Descriptive & Numerical Statistics II - Lecture

Descriptive & Numerical Statistics - Example Problem Set

Descriptive & Numerical Statistics - Example Solution Narrative

3

24

Descriptive & Numerical Statistics I

Descriptive & Numerical Statistics II

HW#1 Video Narrative

HW#1 - All Parts Due by 12 midnight; submit files to Canvas in the appropriate Assignment area

HW#1 Partial Solutions - XLSX File Posted After Due Date

3

31

Quiz #1 - Descriptive & Numerical Statistics



3

Sept 1

Probability I


Probability I - Lecture

Probability Example I - Bayes Rule Tutorial

Probability Example II - Probability Tree and Bayes' Rule Tutorial

Probability Example III - Probability Tree and Bayes' Rule Example II

3 & 3A

3

Statistics & Probability


HW#2 Video Narrative

3 & 3A


11
Quiz #2 - Statistics & Probability

Quiz #2 Review Narrative

3 & 3A

Writing Guidelines


14

Random Variables & Sampling Distributions

Random Variables & Sampling Distributions - Lecture

3 & 3A

18

Confidence Intervals & Inference I

Confidence Intervals - Lecture I

Confidence Intervals - Example I

3 & 3A


21

Confidence Intervals & Inference II

Confidence Intervals - Lecture II

Confidence Intervals - Example II

HW#3 Due

HW#3 - Video Narrative


3 & 3A



28

Quiz #3 - Confidence Intervals & Inference



Quiz #3 Review Narrative



3 & 3A
Oct 3-6
Fall Break
Fall Break
Fall Break
12
Sample Size Determination

Hypothesis Testing I

Sample Size Determination Lecture


Sample Size Determination Example

Hypothesis Testing Lecture I


3 & 3A

19


Hypothesis Testing II

Hypothesis Testing Z tests - Example


Hypothesis Testing Lecture II


Hypothesis Testing-Example

3 & 3A



23

Hypothesis Testing



HW #4 Due Hypothesis Testing



3 & 3A
Nov 2
Hypothesis Testing

Quiz #4 - Sample Size Determination & Hypothesis Testing


3 & 3A





9



Forecasting Lecture I

Forecasting Lecture II - Error Measurement

Forecasting Example I

7

Naive Forecasting Video Tutorial

Forecasting - Moving Average Video Tutorial
16


Linear Regression

Linear Regression Lecture

Linear Regression Example
 

HW#5 Due

6

23
Forecasting and Linear Regression
Review
6 & 7
30
Quiz #5 - Forecasting and Linear Regression

Final Exam will be posted in Canvas by 5 pm on Dec 2nd & will be due by 12 midnight Dec 7th


Quiz #5 - Forecasting and Linear Regression

Please peruse the Final Exam Review
Sheet posted on XXX to prepare for the Final Exam.

6 & 7

Dec 7

Final Exam Due by 12 midnight Dec 7th

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