# Interpret Population and Sample Variances in Google Sheets

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In this Free Guided Project, you will:

Understand variance and what it tells us.

Conduct an analysis of variance on the population and several samples.

Conduct a t-test to examine the difference between two groups when the variance is not known.

Showcase this hands-on experience in an interview

2 hours
Intermediate
Split-screen video
English
Desktop only

The term “analysis of variance” might sound like a sophisticated data science technique and while that may be true some of the time, for the most part analysis of variance is a basic descriptive statistical tool to understand differences between groups in a data set and to learn whether a sample pulled from a larger population is statistically valid because it fairly represents the entire data set. Interpreting variance statistics accurately can mean the difference between finding actions in your data and not finding any. In your Interpret Population and Sample Variances in Google Sheets project, you will gain hands-on experience generating variance statistics, interpreting them, and you will perform a t-test to approach understanding differences in two samples when the variance is unknown. 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 further your business intelligence goals by confidently analyzing and interpreting variance in a data set using any spreadsheet software. 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.

Requirements

## Skills you will develop

Statistical SignificanceRisk MitigationBusiness IntelligenceUnderstanding VarianceLeveraging Statistics

## 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 variance statistics and what they report.

2. Explore variance calculations and how they support understanding a data set.

3. Consider use cases for analysis of variance, import data into Google Sheets and evaluate the data set.

4. Conduct an analysis of variance.

5. Conduct a t-test and report the findings.