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Opiniones y comentarios de aprendices correspondientes a Using Descriptive Statistics to Analyze Data in R por parte de Coursera Project Network

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Acerca del Curso

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....
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1 - 8 de 8 revisiones para Using Descriptive Statistics to Analyze Data in R

por Rajkumar R

18 de jul. de 2020

Enjoyed practicing

por Jesus M Z F

20 de jul. de 2020

Good course

por Simbarashe W

19 de jul. de 2020

It was a bit challenging to follow towards the end, but overall it was a good project.

por Rodrigo G Z

28 de ago. de 2020

Concise and direct with cool tips on the way

por TUSHAR R

2 de oct. de 2020

I explore new things there and learn new thing.

por Karlo A L

6 de oct. de 2020

It was easy enough to follow.

por Surbhi K

7 de oct. de 2020

this courseis nice

por Deepak K

5 de nov. de 2020

Thank You