Statistics for Business: Course Syllabus and Study Guide

Course Overview

Course Description and Goals

This course provides students with an introduction to the basic concepts and ideas in statistics, with a focus on applications in business and economics. Students will learn to analyze data using tools such as Excel, understand probability theory, theoretical probability distributions, sampling distributions, estimation, confidence intervals, hypothesis testing, and linear regression and correlation. The course is designed to develop statistical thinking and inquiry skills, enabling students to interpret and communicate statistical results effectively.

• Statistical Inquiry: Students will be able to apply appropriate concepts, tools, and techniques of scientific inquiry.

• Communication: Students will be able to describe how natural scientific, mathematical, and/or computational methods function as mechanisms for inquiry.

• Interdisciplinary Application: Students will be able to explain the interaction between the context of their SI-Elective course and other scientific disciplines or the broader society.

Prerequisites

• A grade of C or better in MAT 130 (or equivalent) is required to enroll in this course.

Textbook and Technology

Required Textbook

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

• MyLab Statistics online learning platform is required for homework and quizzes.

Required Technology

• A computer or tablet with reliable internet access for course materials, homework, and quizzes.

• Excel is required for data analysis and Excel-based projects.

• Access to MyLabStat for online assignments and quizzes.

• DePaul email and D2L (course management system) for communication and updates.

Recommended Technology

• A basic calculator may be useful for homework, but Excel will be primarily used.

Course Topics

• Descriptive Statistics: Methods for summarizing and describing sets of data.

• Probability: Basic probability theory and rules.

• Random Variables and Distributions: Theoretical probability distributions and their applications.

• Sampling Distributions: Understanding the distribution of sample statistics.

• Estimation and Confidence Intervals: Making inferences about population parameters.

• Hypothesis Testing: Procedures for testing claims about population parameters.

• Regression and Correlation: Analyzing relationships between variables using linear regression.

Assignments and Grading

Grading Distribution

Grade	Percentage
A	93% – 100%
A-	90% – 92%
B+	87% – 89%
B	83% – 86%
B-	80% – 82%
C+	77% – 79%
C	73% – 76%
C-	70% – 72%
D+	67% – 69%
D	60% – 66%
F	< 60%

Assignment Types

• MyLabStat Homework and Quizzes: Online assignments to reinforce concepts and provide practice.

• Excel Projects: Applied data analysis projects using Excel to solve business-related problems.

• Midterm Exams: Two midterms, each worth 15% of the final grade.

• Final Exam: Cumulative exam covering all course topics, worth 25% of the final grade.

Expectations and Policies

• Active participation in class and group work is expected.

• Timely completion of assignments and responsiveness to communication.

• Academic integrity is strictly enforced; plagiarism and unauthorized collaboration are prohibited.

• Collaboration is allowed for MyLabStat homework and Excel projects, but each student must submit their own work.

• Attendance is required for all class meetings.

Support and Resources

• Office Hours: Available at Lincoln Park and Loop campuses, as well as by appointment.

• Tutoring: MAT 137 tutoring available; details posted on D2L.

• Accommodations: Reasonable accommodations provided for students with disabilities or exceptional circumstances.

• Center for Students with Disabilities (CSD): Register for support at go.depaul.edu/csd.

• Dean of Students Office (DOS): Support for urgent needs and personal crises at go.depaul.edu/dos.

Key Formulas and Concepts

Descriptive Statistics

• Mean: $\bar{x} = \frac{1}{n} \sum_{i=1}^{n} x_i$

• Variance: $s^2 = \frac{1}{n-1} \sum_{i=1}^{n} (x_i - \bar{x})^2$

• Standard Deviation: $s = \sqrt{\frac{1}{n-1} \sum_{i=1}^{n} (x_i - \bar{x})^2}$

Probability

• Probability of Event A: $P(A) = \frac{\text{Number of favorable outcomes}}{\text{Total number of outcomes}}$

• Conditional Probability: $P(A|B) = \frac{P(A \cap B)}{P(B)}$

Sampling Distributions

• Standard Error of the Mean: $SE = \frac{\sigma}{\sqrt{n}}$

Confidence Intervals

• Confidence Interval for Mean (Normal Distribution): $\bar{x} \pm z^* \frac{\sigma}{\sqrt{n}}$

Hypothesis Testing

• Test Statistic (Z-test): $z = \frac{\bar{x} - \mu_0}{\sigma / \sqrt{n}}$

Regression

• Simple Linear Regression Equation: $y = \beta_0 + \beta_1 x + \epsilon$

Example Application

• Business Decision Making: Use hypothesis testing to determine if a new marketing strategy increases average sales.

• Data Analysis: Apply regression analysis to predict future sales based on advertising expenditure.

Additional info: This syllabus covers all major topics relevant to a college-level Statistics for Business course, including prerequisites, course goals, required materials, grading, and academic integrity policies. The formulas and examples provided are standard for introductory statistics courses in business.