By the end of this project, you will create a data quality report file (exported to Excel in CSV format) from a dataset loaded in R, a free, open-source program that you can download. You will learn how to use the following descriptive statistical metrics in order to describe a dataset and how to calculate them in basic R with no additional libraries.
Using Descriptive Statistics to Analyze Data in R
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Using Descriptive Statistics to Analyze Data in R
Instructor: Dr. Nikunj Maheshwari
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4.6
(90 reviews)
Beginner level
Recommended experience
1.5 hours
Learn at your own pace
Hands-on learning
What you'll learn
Learn how to calculate descriptive statistical metrics in order to describe a dataset in basic R
Create a data quality report file (exported to Excel in CSV format) from a dataset loaded in R
Skills you'll practice
Details to know
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Taught in English
No downloads or installation required
Only available on desktop
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About this Guided Project
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:
Load and view a real-world dataset in RStudio (5 min)
Calculate Measure of Frequency metrics (5 min)
Calculate Measure of Central Tendency metrics (6 min)
Calculate Measure of Dispersion metrics (4 min)
Calculate additional data quality metrics (6 min)
Calculate descriptive statistics on all columns (10 min)
Generate a data quality report file (8 min)
Recommended experience
The learner should know how information is stored in rows and columns in a table.
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Available only on desktop
This Guided Project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.
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