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Analyze Predictor Impact Using Regression in Minitab

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Analyze Predictor Impact Using Regression in Minitab

Instructor: EDUCBA

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5 hours to complete
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Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

5 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Analyze how multiple predictors influence a response using regression models.

  • Interpret and compare regression outputs in Minitab for model selection.

  • Translate statistical results into actionable business insights.

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Recently updated!

February 2026

Assessments

6 assignments

Taught in English

Build your subject-matter expertise

This course is part of the Minitab Applied Statistics & Hypothesis Testing Mastery Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 2 modules in this course

By the end of this course, learners will be able to analyze how multiple predictors influence a response variable, interpret regression outputs using Minitab, compare alternative regression models, and translate statistical findings into actionable business insights. Learners will develop the ability to evaluate predictor significance, visualize relationships, and select appropriate regression models to support data-driven decision-making.

This course provides a practical, hands-on approach to regression analysis through a real-world Tech Mahindra case study. Rather than focusing on theory alone, learners work step-by-step through an end-to-end analytics project—starting from problem framing and exploratory analysis to model refinement and comparison. Using Minitab, learners gain experience interpreting regression coefficients, p-values, and visual diagnostics such as scatter plots to understand predictor–response relationships. What makes this course unique is its strong business orientation and project-based structure. Learners not only build and compare linear and quadratic regression models but also learn how to justify model choices based on both statistical performance and business relevance. This course is ideal for professionals and students seeking to strengthen applied regression skills and confidently use Minitab for real-world analytical challenges.

This module introduces learners to a real-world regression project using Minitab, focusing on clearly defining the business problem, identifying response and predictor variables, and building an initial regression model. Through the Tech Mahindra case study, learners explore how statistical analysis connects to business decision-making using exploratory data analysis, regression output interpretation, and visualization techniques.

What's included

5 videos3 assignments

5 videosTotal 44 minutes
  • Introduction to Project8 minutes
  • Case Study - Tech Mahindra6 minutes
  • Regression Model and Output - Tech Mahindra10 minutes
  • Scatter Plot - Tech Mahindra11 minutes
  • Case Study - Tech Mahindra 18 minutes
3 assignmentsTotal 50 minutes
  • Framing the Business Problem with Regression30 minutes
  • Project Context & Business Case10 minutes
  • Building and Visualizing the Initial Regression Model10 minutes

This module guides learners through refining regression models by reassessing predictors, validating assumptions, and comparing alternative model forms. Using advanced iterations of the Tech Mahindra case study, learners evaluate linear and quadratic regression models, apply visual and statistical comparison techniques, and select models that balance analytical accuracy with business interpretability.

What's included

5 videos3 assignments

5 videosTotal 39 minutes
  • Case Study - Tech Mahindra 26 minutes
  • Case Study - Tech Mahindra 37 minutes
  • Case Study - Tech Mahindra 49 minutes
  • Comparison of Linear and Quadratic Regression Models8 minutes
  • Comparison with Scatter Plots9 minutes
3 assignmentsTotal 50 minutes
  • Model Refinement and Comparative Analysis30 minutes
  • Exploring Predictor–Response Relationships10 minutes
  • Comparing Regression Models for Better Decisions10 minutes

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Instructor

EDUCBA
1,591 Courses326,930 learners

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