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Statistical Tests for Market Research

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Statistical Tests for Market Research

This course is part of multiple programs.

Instructor: LearningMate

Included with

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2 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

2 hours to complete

Flexible schedule

Learn at your own pace

2 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

2 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Analyze market research data, apply t-tests in Excel to compare groups, interpret results, and make data-driven business recommendations.

Skills you'll gain

Tools you'll learn

Statistical Software

Details to know

Shareable certificate

Add to your LinkedIn profile

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Build your subject-matter expertise

This course is available as part of

When you enroll in this course, you'll also be asked to select a specific program.

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

This course builds essential statistical analysis capabilities for market research professionals. Learners will develop a strong understanding of statistical package functionality and master techniques for comparing group differences through hypothesis testing. You'll move beyond raw data to defensible insights by learning not just how to run a statistical test, but why it matters and what it means for the business.

Through practical, hands-on application in real-world scenarios—such as A/B testing and customer satisfaction analysis—you will build the analytical skills needed to draw statistically valid conclusions from research data. You will master the two-sample t-test in Microsoft Excel, learning to interpret key metrics like the p-value and translate them into clear, actionable business recommendations. This course provides the foundational skills to use statistical evidence to answer critical business questions, validate assumptions, and contribute to a culture of data-driven decision-making in your organization.