Linear Regression and Modeling Course Syllabus

Overview: This course provides a practical, Excel-based introduction to linear regression and modeling, designed for business professionals and analysts. Over five modules, learners will build foundational skills in regression analysis, interpret results, and apply techniques to real-world business problems. Each module requires approximately 3–5 hours, with a total time commitment of 15–25 hours. The course concludes with a hands-on project, enabling learners to demonstrate proficiency in building and evaluating regression models using Excel—no coding required.

Module 1: Introduction to Linear Regression

Estimated time: 4 hours

• Understanding dependent vs. independent variables
• Creating and interpreting scatterplots
• Measuring correlation
• Building your first regression model in Excel

Module 2: Estimating the Regression Line

Estimated time: 4 hours

• Introduction to Ordinary Least Squares (OLS)
• Calculating residuals
• Finding the best-fit line
• Hands-on regression calculation by hand and in Excel

Module 3: Evaluating the Model

Estimated time: 4 hours

• Interpreting R² and adjusted R²
• Assessing model strength
• Hypothesis testing for regression coefficients
• Interpreting regression output in Excel

Module 4: Model Assumptions and Diagnostics

Estimated time: 4 hours

• Checking linearity and independence assumptions
• Assessing homoscedasticity
• Evaluating normality of residuals
• Performing residual analysis in Excel

Module 5: Business Applications of Regression

Estimated time: 5 hours

• Using regression for forecasting
• Applying regression in marketing analysis
• Supporting pricing strategy decisions
• Working through real-world business case studies

Module 6: Final Project

Estimated time: 6 hours

• Build a regression model using a real business dataset
• Interpret coefficients and assess model validity
• Submit a report with insights and recommendations

Prerequisites

• Basic understanding of statistics
• Familiarity with Excel (formulas and charts)
• High school-level mathematics

What You'll Be Able to Do After

• Understand the fundamentals of linear regression and its assumptions
• Use regression models to analyze relationships between variables
• Interpret regression coefficients and determine model validity
• Apply regression analysis in real-world business scenarios
• Use Excel to build and evaluate regression models confidently