Type 1 and Type 2 Error Analysis in Google Sheets

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Coursera Project Network
In this Free Guided Project, you will:

Understand Type 1 and Type 2 errors and the importance of recognizing them to mitigate risk.

Develop a hypothesis and prepare data for testing in Google Sheets.

Conduct a t-test and interpret the test statistic in Google Sheets.

Showcase this hands-on experience in an interview

Clock2 hours
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

Data has the power to inform decision-making to move us toward our personal, professional, and organizational goals. However, there is a risk involved in data-driven decision making when we are not confident in the interpretation of analytical test findings. Gaining that confidence in the data we use for decision-making requires us to be able to recognize Type 1 and Type 2 analysis errors. In this project you will gain hands-on experience with the principles of developing a hypothesis, conducting a t-test, interpreting test results, and recognizing Type 1 and Type 2 errors. To do this you will work in the free-to-use spreadsheet software Google Sheets. By the end of this project, you will be able to recognize Type 1 and Type 2 errors to improve confidence using data for decision-making. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.


Some familiarity with hypothesis testing would be helpful, but is not required.

Skills you will develop

Validity (Statistics)Business AnalyticsResearch MethodologyBusiness IntelligenceInsight Mining

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Review Type 1 and Type 2 errors and how identifying them mitigates risk.

  2. Review the fundamentals of hypothesis testing and the process of interpreting results.

  3. Identify use cases for hypothesis testing.

  4. Access Google Sheets, import data, develop a hypothesis, and prepare data for testing.

  5. Conduct a t-test and interpret the test statistic.

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step



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Frequently Asked Questions

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