Data science tools: Instructions: Compose a well-developed post (< 100 words) that is comprehensive in answering questions posed below. Demonstrate integration of the required reading, other course materials, critical thinking, scholarly or peer-reviewed sources (as applicable), using APA format.
Plagiarism: According to the Council of Writing Program Administrators, “Plagiarism occurs when a writer deliberately uses someone else’s language, ideas, or other original (not common-knowledge) material without acknowledging its source.”  Any of these activities constitutes plagiarism: directly copying and pasting from a source without citation; paraphrasing from a source or sources without citation; turning in a paper, or sections of a paper, known to be written by someone other than the student; unauthorized multiple submissions of the same work in more than one course
1) Importance of Programming: Write a short paragraph (< 100 words) on the importance of programming in data analytics. Also, write the advantage of open-source language like R over other licensed programming software.
2) Objects: Write a short paragraph on various R-objects and describe the linear hierarchical difference between them. (<100 words)
3) Data Transformations: Write a short paragraph (< 100 words) on the importance of data transformation and various techniques you learned from Chapter 3 of the book.
4) Data Visualization: Write a short paragraph (< 100 words) on the importance of data visualization in analytics. Describe your most favorite feature of the ggplot2 library.
5) Exploratory Data Analysis: Write a short paragraph (< 100 words) on what you understand by exploratory data analysis.
6) Three Interesting Techniques in EDA: Write a short paragraph (< 100 words) on the three interesting techniques that you learned during this week.
7) Advantage of various formats of data :Write a short paragraph (< 100 words) on the various formats of data such as .csv, .txt, .json etc.
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