Using Descriptive Statistics to Analyze Data in R

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In this Guided Project, you will:

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

Clock1.5 hours
BeginnerBeginner
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

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. - minimum value - maximum value - average value - standard deviation - total number of values - missing values - unique values - data types You will then learn how to record the statistical metrics for each column of a dataset using a custom function created by you in R. The output of the function will be a ready-to-use data quality report. Finally, you will learn how to export this report to an external file. A data quality report can be used to identify outliers, missing values, data types, anomalies, etc. that are present in your dataset. This is the first step to understand your dataset and let you plan what pre-processing steps are required to make your dataset ready for analysis. 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.

Skills you will develop

Data QualityStatisticsR Programming

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. Load and view a real-world dataset in RStudio

  2. Calculate “Measure of Frequency” metrics

  3. Calculate “Measure of Central Tendency” metrics

  4. Calculate “Measure of Dispersion” metrics

  5. Use R’s in-built functions for additional data quality metrics

  6. Create a custom R function to calculate descriptive statistics on any given dataset

  7. Export the results of the descriptive statistics to a data quality report file

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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