Software and Tools

R Statistical Software

Free statistical computing environment (optional - Binder available)

Download R

RStudio IDE

Integrated development environment for R (optional)

Download RStudio

Binder (Recommended)

Browser-based R environment - no installation required!

Launch Binder

Course Materials

Lecture Recordings

Access all recorded lectures

View Recordings

Canvas Course Site

All course materials and assignments

Access Canvas

Textbooks and References

📚 Required Materials

No textbook is required for this course. All necessary materials are provided through course content and online resources.

📖 Supplementary Textbooks (Optional)

Daniel, Wayne W., and Chad L. Cross. Biostatistics: a foundation for analysis in the health sciences. Wiley, 2018.
Zar, Jerrold H. Biostatistical analysis. Princeton-Hall, New Jersey (1999).
McClave, James T., and Terry T. Sincich. Statistics. Pearson Higher Ed, 2017.
Li, Jerome CR. Statistical inference. Vol. 1. Ann Arbor: Edwards Brothers, 1964.
Arora, P. N., and P. K. Malhan. Biostatistics. Himalaya Pub. House, 2010.
Hodges Jr, Joseph Lawson, and Erich Leo Lehmann. Basic concepts of probability and statistics. Society for Industrial and Applied Mathematics, 2005.
Hacking, Ian. Logic of statistical inference. Cambridge University Press, 2016.

Online Learning Resources

R for Data Science

Free online book by Hadley Wickham

Read Online

Quick-R

Quick reference for R commands and functions

Visit Site

Stack Overflow

Programming Q&A community for R help

Browse Questions

R Packages for Statistical Analysis

📦 Pre-installed in Binder

All necessary packages are already installed in the Binder environment. No setup required!

Essential Packages (if using local R)

# Install essential packages for local R installation
install.packages(c("ggplot2", "dplyr", "tidyr", "readr", 
                   "knitr", "rmarkdown"))

Package	Purpose	Key Functions
ggplot2	Data visualization	ggplot(), geom_point(), geom_histogram()
dplyr	Data manipulation	filter(), select(), mutate(), summarize()
tidyverse	Collection of data science packages	Includes ggplot2, dplyr, tidyr, readr
knitr	Dynamic report generation	kable(), opts_chunk()

Practice Datasets

Built-in R Datasets

iris: Flower measurements for classification and visualization
mtcars: Motor car data for regression practice
PlantGrowth: Plant growth under different conditions
chickwts: Chicken weights by feed type
ToothGrowth: Tooth growth in guinea pigs

Course Datasets

LA_Data.csv: Statistics data for Week 1 assignment
Additional datasets: Provided weekly as needed

Getting Help

📧 Course Support

Mohammadreza Narimani

Teaching Assistant

mnarimani@ucdavis.edu

Office Hours: Thursdays 10 AM - 12 PM

Join Zoom Office Hours

💡 R Help Resources

Built-in Help: Use ?function_name or help(function_name)
Canvas Discussion: Post questions on the course discussion board
Binder Environment: All packages pre-installed, no setup issues
Peer Support: Form study groups with classmates

🎓 UC Davis Resources

Learning Skills Center: Statistics tutoring available
Library Research Support: Data analysis assistance
Student Disability Center: Accommodations as needed