Data quality in R programming

Description

This project deals with issues that come up with data collection. Use install.packages(“ggplot2”) to get datasets about diamonds that are shipped with the ggplot2 package. Cover in the project the following:There is a surprisingly cheap 5 carat diamond, and some cheap 3 carat diamonds. How can we identify those points? Use an interactive scatterplot to identify outliers in these variables. Check prices, carat and other information and think about if any of the outliers can be due to data errors. Discuss the following: How can you tell if the data is an outlier or if it is something important?Which data is the noise and how is the noise different from outliers? When there are missing values, explain the pros and cons of the following strategies: Elimination of Data ObjectsEstimation of Missing Values What are the limitations of analyzing real data with missing values and why is it impossible to really know such data?

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