Course Overview

Introduction to Business Statistics

This course, MAT 137 (Business Statistics), provides an introduction to the fundamental concepts and methods of statistics as applied to business contexts. Students will learn to analyze data, apply probability and statistical inference, and use regression models, primarily through the use of Microsoft Excel.

• Course Meetings: Mondays and Wednesdays, 10:10 AM – 11:40 AM

• Instructor: Professor Phil Yates

• Textbook: Statistics for Business and Economics, 14th Edition, by McClave, Benson, and Sincich

• Calculation Tool: Microsoft Excel (no calculators required)

Course Description and Goals

Scope of the Course

The course covers basic statistical concepts, data analysis using Excel, theoretical and sampling distributions, estimation, hypothesis testing, and regression analysis. Emphasis is placed on interpreting statistical results and applying them to business decision-making.

• Prerequisites: Completion of MAT 130 or adequate performance on the Mathematics Diagnostic Test

• Applications: Real-world business data and scenarios

Learning Outcomes

• Recognize and explain statistically based results from real data and evaluate the validity of conclusions.

• Use statistical software (Excel) to produce and interpret graphical displays and statistical summaries.

• Understand the roles of variability and randomness in data interpretation.

• Explain ethical issues in statistical practice and research design.

• Measure association strength between variables and identify confounding or interacting variables.

• Apply statistical inference methods, including confidence intervals and hypothesis testing.

• Produce appropriate graphical and numerical descriptive statistics for different data types.

• Apply probability rules and knowledge of random variables to business problems.

• Recognize and apply the Central Limit Theorem (CLT).

• Make statistical inferences about population means and proportions.

• Use regression models for analysis and prediction.

Writing Requirements

Academic Communication in Statistics

Students are expected to demonstrate effective written communication, including summarizing, paraphrasing, and technical accuracy. Assignments will include formal writing (essays, reports) and supplemental elements (problem sets, code, graphs, and statistical formulas).

• Minimum of 5–10 pages of writing distributed across assignments and projects.

• Emphasis on clarity, technical accuracy, and proper citation.

Grading Structure

Assessment Components

• Excel Activities (15%): In-class assignments using Excel, submitted via D2L.

• Lecture Assignments (30%): Regular homework assignments, completed online via MyLabsPlus (MLP).

• Midterm Exam (25%): In-class exam (scheduled for February 9).

• Final Exam (30%): Comprehensive final (scheduled for March 18).

Grading Scale

Expected Student Workload

• Minimum of 10 hours per week, including 3 hours in class and 7 hours outside class for readings, assignments, and study.

University Policies & Resources

Academic Integrity

• Students must adhere to DePaul’s Academic Integrity Policy, which prohibits cheating, plagiarism, fabrication, and other forms of academic misconduct.

Support Services

• Library Resources: Access to scholarly articles, books, and research help.

• Center for Students with Disabilities: Accommodations and support for registered students.

• Counseling & Psychological Services: Free, confidential counseling for students.

• Dean of Students: Support for academic and personal challenges, and administration of the Code of Student Responsibility.

Weekly Schedule and Topics

Course Outline by Week

Key Topics Covered

• Chapter 1: Statistics, Data, and Statistical Thinking

• Chapter 2: Methods for Describing Sets of Data

• Chapter 3: Probability

• Chapter 4: Random Variables and Probability Distributions (including Binomial Distribution)

• Chapter 5: Sampling Distributions and the Central Limit Theorem

• Chapter 6: Inferences Based on a Single Sample: Estimation with Confidence Intervals

• Chapter 7: Inferences Based on a Single Sample: Tests of Hypotheses

• Chapter 11: Simple Linear Regression

Summary

This syllabus outlines a comprehensive introduction to business statistics, emphasizing both conceptual understanding and practical application using Excel. Students will develop skills in data analysis, probability, statistical inference, and regression, preparing them for further study or professional application in business contexts.