Using Descriptive Statistics to Analyze Data in R

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In diesem angeleitetes Projekt werden Sie:

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
BeginnerAnfänger
CloudKein Download erforderlich
VideoVideo auf geteiltem Bildschirm
Comment DotsEnglisch
LaptopNur Desktop

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.

Kompetenzen, die Sie erwerben werden

  • Data Quality
  • Statistics
  • R Programming

Schritt für Schritt lernen

In einem Video, das auf einer Hälfte Ihres Arbeitsbereichs abgespielt wird, führt Sie Ihr Dozent durch diese Schritte:

  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

Ablauf angeleiteter Projekte

Ihr Arbeitsbereich ist ein Cloud-Desktop direkt in Ihrem Browser, kein Download erforderlich

Ihr Dozent leitet Sie in einem Video mit geteiltem Bildschirm Schritt für Schritt an.

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