Faculty

BUSI-2305 Business Statistics

George Frederickson

Credit Spring 2026

Section(s)

BUSI-2305-003 (15675)
LEC DIL ONL DIL

BUSI-2305-008 (15679)
LEC DIL ONL DIL

BUSI-2305-011 (15682)
LEC DIL ONL DIL

BUSI-2305-012 (15683)
LEC DIL ONL DIL

BUSI-2305-017 (34089)
LEC CYP ONL DIL

LEC M 10:30am - 11:50am CYP CYP5 2223

Course Requirements

Welcome to Biz Stats! I believe you will learn a great deal about using statistics in the business world and, hopefully, have a little fun along the way.

This is a difficult course if you fall behind. DON'T FALL BEHIND! I'll do all I can to help you get through this course and don't be surprised if you earn an A. A lot of students do. I hope you do as well.

To get started:

1. Carefully read through the Syllabus

2. Review the Course Calendar and the Homework Assignments Schedule. These are both located in the same place as the Syllabus. Please note the extra credit Orientation Quiz is due by the end of the first week.

3. Explore the rest of the course content in Blackboard. Notice the homework problem solutions are provided for you as well as a bunch of extra credit quizzes that you make re-take until you earn the full credit. These are very good practice for the exams.

4. Once you feel comfortable with what's in Blackboard, start the assigned reading, then do the assigned homework problems checking your answers against the solutions. If you get stuck, contact me for help.

5. After completing the homework, then I suggest you complete the extra credit quiz and then once you feel really good about the material, take the exam.

6. Keep on schedule per the calendar!! Falling behind is VERY dangerous in an on-line course.

7. Please shoot me an email if you need help on a problem, or want to schedule a call with me or in person time. If urgent, text me. I am available to help you successfully complete this course!

8) AI Policy
Introduction
This course encourages the use of generative artificial intelligence (GAI) tools, such as
ChatGPT and similar platforms, as a supplemental resource to enhance your learning,
research, and writing process. However, students are expected to critically evaluate AI-
generated content using the concepts and analytical skills learned in class.
Rationale
GAI can assist in brainstorming, organizing, and revising economic writing, but it may
provide inaccurate or misleading information, especially in data interpretation or
theoretical application. Developing your judgment about AI-generated output is essential
to becoming a thoughtful and responsible user of emerging technologies.
Definition of GAI
GAI refers to tools that can produce text, code, images, or other content in response to
user prompts. In this course, GAI includes programs like ChatGPT, Claude, Bing AI, and
others capable of generating economic explanations, summaries, or writing assistance.
Resources: To support responsible GAI use, you may consult the following:
● ACC Library’s GAI Toolkit
● Purdue OWL on AI writing assistance
● In-class demonstrations of ChatGPT usage and limitations
● Instructor office hours for GAI usage feedback
Assessment
You may use GAI to help generate ideas or organize drafts for assignments (e.g., paper
proposals, outlines), but the final submission must reflect your own understanding. In
assessments such as the term paper or final presentation, your ability to apply cour

Best,

Professor Fred.

Readings

Statistical Techniques in Business and Economics

Douglas Lind & William Marchal, Samuel Wathen, 17th, 18th or 19th edition.

Irwin McGraw-Hill

You will not need any on-line modules.

Course Subjects

What is Statistics
Describing Data in Tables and Distributions
Describing Data Numerically
Displaying and Exploring Data
Probability Concepts
Probability Distributions
Continuous Probability Distributions
Sampling Methods and the Central Limit Theorm
Estimation and Confidence Intervals
One-Sample Hypothesis Tesing
Two-Sample Hypothesis Testing
Linear Regression and Correlation
Multiple Regression

Student Learning Outcomes/Learning Objectives

This statistics course is designed for business majors. Topics include organization of measurements, determining measures of central tendency, discrete distributions, continuous distributions, confidence intervals, variability, counting, probability, statistical inference, hypothesis testing (large and small samples), simple and multiple regression and correlation analysis, time series, nonparametric methods and statistical quality control. The objective of this course is to provide students with a basic understanding of statistical procedures, techniques and applications as used in business.