Chevron Left
Using Descriptive Statistics to Analyze Data in R に戻る

Coursera Project Network による Using Descriptive Statistics to Analyze Data in R の受講者のレビューおよびフィードバック

4.6
84件の評価

コースについて

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....
フィルター:

Using Descriptive Statistics to Analyze Data in R: 1 - 8 / 8 レビュー

by Rajkumar R

2020年7月18日

by Jesus M Z F

2020年7月20日

by Simbarashe W

2020年7月19日

by Rodrigo G Z

2020年8月28日

by TUSHAR R

2020年10月2日

by Karlo A L

2020年10月6日

by Surbhi K

2020年10月7日

by Deepak K

2020年11月5日