Overview

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By the end of this course, you'll be able to run a regression analysis in Excel, SPSS, and R, interpret the results with confidence, and turn them into a story that drives real decisions. You'll uncover the relationships hidden in your data, choose the right type of regression for any question, check whether your model can be trusted, and separate genuine cause from mere coincidence. Data can feel overwhelming: the patterns hide, and it's hard to tell what's real from what's just chance. This course changes that. Guided by a senior data scientist who specializes in turning numbers into stories anyone can understand, you'll move step by step from the fundamentals of ordinary least squares to diagnosing model assumptions, handling outliers, and avoiding the most common analytical mistakes. What makes this course different is its focus on communication as much as calculation. Running the model is only half the job; the real skill is explaining what it means. You'll build clean charts, translate coefficients into dollars and decisions, and present findings that stakeholders actually remember. Whether you're a beginner or brushing up, you'll leave able to make your data talk.

Syllabus

Laying the Groundwork

Before you can trust a single regression result, you need to know what the method actually does and when to reach for it. In this module, you'll see what regression reveals, describe how ordinary least squares finds the line of best fit, and select the right regression type for the question in front of you.

Run Your First Regression

Knowing the theory is one thing, but real confidence comes from running a regression yourself. In this module, you'll choose the right software for your project and run your first linear regressions in Excel, SPSS, and R so you can locate the values that matter in any output.

Interpret and Visualize Your Results

A regression is only as good as your ability to read it, and a strong-looking model can still mislead you. In this module, you'll interpret the core output values, check the assumptions behind them, separate correlation from causation, and handle the outliers and mistakes that quietly distort results.

Share Your Findings with Confidence

The best analysis in the world falls flat if your audience can't see why it matters. In this module, you'll build clean charts, translate your results into business language, and frame a data story that moves stakeholders to act.