Using Regression to Forecast in Microsoft Excel

Learn how to apply regression techniques in Excel to predict trends and make data-driven forecasts
What you'll learn
Learn how to choose the right regression method for different data types.
Apply simple linear regression to analyze straight-line trends in data.
Understand and use the regression equation to describe relationships.
Use the LINEST function to calculate best-fit values and interpret results.
Forecast future values using Excel tools like TREND and the Fill Handle.
Extend data trends using the Series command for linear projections.
Analyze sales and advertising data with case-based forecasting models.
Apply exponential, logarithmic, and power regressions for curved trends.
Use GROWTH and LOGEST functions for nonlinear trend forecasting.
Perform multiple regression analysis to track several variables at once.
Requirements
Microsoft Excel (Office 2021 or Microsoft 365) installed.
Basic knowledge of Excel (e.g., entering data, simple calculations).
Access to a computer with a stable internet connection.
No prior advanced Excel skills required; suitable for beginners.
Description
This course is designed for learners who want to apply regression analysis in Excel to uncover trends, analyze relationships, and forecast future outcomes with confidence. Using the powerful tools available in Microsoft Excel (Office 2021 and Microsoft 365), students will develop hands-on skills in both linear and nonlinear regression techniques, enabling them to make data-driven decisions across a variety of professional and academic contexts.The course begins by exploring how to choose the most appropriate regression method based on data type and trends. Students will learn to use simple linear regression to model relationships, interpret the regression equation, and calculate best-fit values using functions such as LINEST and TREND. Through practical examples-such as analyzing the link between sales and advertising-students will forecast future values using the Fill Handle, Series command, and Excel's built-in forecasting tools.As the course progresses, learners will explore more complex models, including exponential, logarithmic, power, and polynomial regression. They'll gain experience using Excel's GROWTH, LOGEST, and other forecasting functions to model nonlinear data. The course concludes with an introduction to multiple regression analysis, allowing students to analyze how several variables interact in predicting outcomes.By the end of this course, students will be able to select, apply, and interpret regression models in Excel to identify patterns and build reliable forecasts for real-world applications.
Who this course is for
This course is for students learning data analysis using Excel.
Ideal for business professionals who need to forecast trends.
Great for marketers analyzing sales and advertising results.
Useful for analysts tracking seasonal or long-term changes.
Made for Excel users ready to apply regression in real-world tasks.
Perfect for finance or economics students studying predictive tools.
Designed for those comparing multiple regression types in Excel.
A fit for anyone modeling growth using exponential or power trends.
Tailored for learners working with both linear and nonlinear data.
Helpful for professionals needing accurate Excel-based forecasting.
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