Introduction to analytics using R, R Studio and R Markdown
Short manual series

Dr. Dee Chiluiza, PhD
Instructor
Northeastern University
Boston, Massachusetts

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Dr. Dee Chiluiza, PhD. I am a part-time instructor at the College of Professional Studies, Northeastern University in Boston, Massachusetts. I teach at both, the undergraduate and Graduate programs in Analytics I have a Bachelor’s degree in sciences from University of Guayaquil, in Ecuador, a Master degree in Coastal Sciences from University of Southern Mississippi, and a PhD degree in Biochemistry and Molecular Biology from Louisiana State University.

Purpose of this work.

This material is for educational purpose only, it currently represents a work in progress. They are based on my teaching experience and learning material I have prepared for my students at Northeastern University.

The students at my classes are learning two major fields at the same time: analytics and programming in R, and this is a big challenge they must accomplish with high levels of excellence in a short period of time, specially at the Master level courses. I have developed a simple strategy to teach both disciplines, helping my students to grow their learning curves in a fun and enjoyable process. I am putting this manual series as a reference and learning resource for my students, and also making it available to other students and instructors.

This work is also part of a book project I am working on.

Until otherwise clearly stated, this material is considered to be draft version.

If you have any questions, please contact me at d.chiluizareyes@northeastern.edu

TABLE OF CONTENTS
Note: Since this is a work in progress, the number of sections and their order can change at anytime.

• Installing R and R Studio

• Using projects to organize R files

• Vectors and Matrix

• Basic Descriptive Statistics

• Categorical variables (analysis and presentation)

• Numerical variables (analysis and presentation)

• Probability (one of the most important concepts in Analytics, if not the most important)

• Using density distributions to analyze continuous data

• Graphs: bar plots

• Graphs: pie charts

• Graphs: Histograms

• Graphs: Box plots

• Graphs: scatter plots

• Introduction to R Markdown

• Basic HTML Codes used in R Markdown (to create your first report)

• Strategies to present graphs and images

• Basic concepts of probability and its applications

• Discrete and normal distributions (probability applications)

• Z scores applications

• Sample size and confidence intervals, making estimations about a population parameter

• Confidence intervals and hypothesis testing

• More to come

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Other recommended links to keep in mind

• My Profile in LinkedIn
www.linkedin.com/in/dchiluiza

• My Spanish poetry and prose book “Bruno con las patas frías”
www.andinart.us/books

• My page at Northeastern University
cps.northeastern.edu/faculty/dee-chiluiza-reyes

• Bachelor of Science in Analytics program at Northeastern University
cps.northeastern.edu/program/bachelor-of-science-in-analytics-boston/

• Master of Professional Studies in Analytics at Northeastern University
cps.northeastern.edu/program/master-of-professional-studies-in-analytics-boston

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Disclaimer: This short series manual project is a work in progress. Until clearly mentioned, these files are considered draft versions.

Dee Chiluiza, PhD
June 2021
Last update: 26 January, 2023
Boston, Massachusetts, USA