DDS8501

Data Science Foundations with R, Zylabs.com 

• Read Chapter 5.   Data Wrangling 

This chapter discusses examining, cleaning, filtering, and general ‘data wrangling,’ which is the topic of this lesson. 

Applied Statistics with Data Analytics (R), Zylabs.com   

• Read Chapter 30: Data Cleansing and Preparation, Section 1: What is data cleansing, Section 2: Missing Values, Section 3: Outliers, Section 4: Standardization and Normalization. 

These sections discusses data cleaning and preparation, which is the topic of this lesson. 

Amelia II: A Program for Missing Data

Honaker, J., King, G., & Blackwell, M. (2011). Amelia II: A program for missing data. Journal of Statistical Software, 45, 1-47. 
This article discusses one of the many tools for generating missing maps in R, a requirement for the assignment. 

Hands-on Exploratory Data Analysis with R: Become an Expert in Exploratory Data Analysis using R Packages 

Datar, R., & Garg, H. (2019). Hands-on exploratory data analysis with R: Become an expert in exploratory data analysis using R packages. O'Reilly Media, Inc. 

• Read Chapter 3: Examining, Cleaning and Filtering 

Content aligns with the topic of this lesson. 

Exploratory Data Analysis Using R & RStudio 

Kumar, R. V. (2021). Exploratory data analysis using R & RStudio. https://www.researchgate.net/profile/Rohit-Kumar-35/publication/354312419_Exploratory_Data_Analysis_using_R_RStudio/links/613086f0c69a4e4879735b4b/Exploratory-Data-Analysis-using-R-RStudio.pdf 

This article provides an example of EDA in R and R Studio.