Welcome to MATH 315

Applied Statistics I - Spring 2026

Dr. Robin Donatello

Overview

  • Meet your instructor
  • Course Objectives
  • Course Materials
  • Class Flow
  • Policies

These slides do not replace the need to read the Syllabus in detail.

Meet your instructor

Dr. Robin Donatello (she/her)

You can address me as “Robin”, “Dr. D”, or some other respectful title that you feel comfortable with.

I have a Doctorate in Public Health (DrPH) Biostatistics from UCLA, but I’m a Chico alum. I double majored in Statistics & Biology, with minor in Chemistry, and a first generation college student who started at Butte College.

My campus life consists of training the next generation of Scientists how to harness the power of Statistics and Data in a responsible and ethical manner, serving as a Research Manager for the Center for Healthy Communities, leading the Data Science Initiative, provide internship experiences for students and faculty, and organizing data analytical support for researchers on and off campus through the Wildcat Data Hub.

When I’m not on campus, typically I’m growing food for my family, out adventuring with my dogs, or getting some game time in. You can learn more about the projects I’m involved in on my website.

Learning Assistants

Khushi and Jayana are Masters in Data Science and Analytics students that will be helping grade, answer questions over Discord or in person at Community Coding, and help out directly in class during open work periods.

Jayana Sarma

Khushi Choudhary

What is this class about?

Statistics in the service of research

Choose your own adventure

In this project-based course, you will have the opportunity to answer questions that you feel passionately about through independent research based on existing data. The course offers a lot of one-on-one support, directed opportunities to work with other students, and training in the skills required to complete a project of your own design. We will use collaborative tools and software that are common in many workplaces and research labs. These skills will prepare you for many different career types.

Tentative topic/module list

  • Writing testable research questions
  • Preparing data for analysis
  • Describing distributions of data - in numbers, words and pictures
  • Bivariate statistical inference (T-test, ANOVA, \(\chi^2\), Correlation)
  • Simple and Multiple regression modeling

Learning goals

  • Develop a testable research question.
  • Understand how to use a codebook to identify data relevant to that question.
  • Process, screen, recode, transform, and clean data.
  • Describe data using visualizations and words.
  • Select and carry out an appropriate statistical analysis.
  • Explain study results and limitations to a non-technical audience.
  • Understand and implement a reproducible research pipeline.
  • Become a data nerd (Optional, but recommended).

Graded Materials

  • 10 Written Assignments: R + Quarto
  • 12 Quizzes: Individual + Group
  • 2 non-cumulative exams
  • Co-authored Research Project
  • Active learning (peer review, learning journal, office hours, asking questions)

All categories carry equal weight (20%) for your final grade.

Course Materials (the stuff)

A variety of learning and working tools

  • I use a combination of tools that are most appropriate for the task or outcome at hand.
  • Homework 1 provides a checklist for getting connected and testing out your tools.
  • It is imperative that you fully complete this assignment ASAP and contact me or the learning assistants with questions.

Class website

https://math315.netlify.app/

  • Contains links to lecture notes, quizzes, homework, shared google folder, other relevant materials.
  • Sometimes links will be broken. Typo’s happen. Notify me via Discord and I’ll get to it asap.

Textbook & Course Packet

  • Open Intro Statistics. Downloadable free PDF
  • The page course packet will be handed out during the second week of classes.
    • Due to the generosity of our Math Department, this will be free for students this term but you will need to supply your own 3 ring binder.
    • You can opt for a PDF version as part of Homework 1.

Content Videos

This course uses lecture videos from a program called Passion Driven Statistics. These videos provide content and coding examples, help set your understanding of the material in the broader context of research.

Discord

  • Used for outside class announcements discussions, meme sharing, homework help and general chatter.
  • EXCELLENT for sharing code problems and helping others debug. 💚 Screenshots
  • I will not answer most class-content based questions through email.
  • Download either the phone app or the desktop app (I use both).
    • Do not rely on remembering to log in via the web browser. You will miss important notifications.

R + R Studio in Jupyter Hub

  • Free version of R Studio in the cloud. I can share materials with you, you can use it for other classes.
  • All you will need is a web browser to use this software.

Google Drive

  • Collaborative research project work
  • Peer reviews
  • Quizzes

Canvas & Gradescope

  • Canvas: Assignment submission, gradebook, class schedule/calendar
  • Gradescope: We will use Gradescope for the actual grading of most assignments. Clicking the assignment submission button in Canvas will take you to Gradescope to submit your assignment, review grading comments, and request regrades. You can also log into Gradescope directly if you wish.

Class Format (how do we use that stuff?)

Before class

  • Watch PDS videos
  • Read textbook sections
  • Course packet work
  • Individual quiz (Sun)

During class

  • Housekeeping
  • Group quiz (Mon)
  • Guided exercises
  • Open work time

After class

  • Work with your research partner on your project
  • Complete the homework

Active Learning

Learning statistics and data science is not a spectator sport. When students ask questions, explain their thinking, or help one another, it improves understanding for everyone. Active participation is therefore an important part of this course.

  • Learning journal (self reflection)
  • Peer reviews
  • Active participation
    • Random call out in class
    • Discord collaboration
    • Attend Office Hours
    • Attend Community Coding

Code of Conduct & My Policies

Everyone is welcome here

It is my intent that students from all diverse backgrounds and perspectives be well-served by this course, that students’ learning needs be addressed both in and out of class, and that the diversity that the students bring to this class be viewed as a resource, strength and benefit.

It is my intent to present materials and activities that are respectful of diversity: gender identity, sexuality, disability, age, socioeconomic status, ethnicity, race, nationality, religion, and culture.

Supportive Learning Environment

I would like to create a learning environment where you feel safe to be pushed outside your comfort zone. That’s where learning happens! To help accomplish this:

  • Let me know if you have a name and/or set of pronouns that differ from those that appear in your official Chico records.
  • Help me pronounce your name as accurately as possible. Corrections and patience are welcome.
  • If you feel like your performance in the class is being impacted by your experiences outside of class, please don’t hesitate to come and talk with me. I am a resource for you.
  • Everyone must agree to treat each other with kindness and respect, understand that we all come from different backgrounds and have different experiences and strengths.
  • When in doubt, assume a positive intent and don’t take things personally.

Collaboration, Plagerism and AI

As an instructor I recognize there are a variety of AI programs available to assist in creating text and writing code. I expect that you also recognize that AI programs are not a replacement for human creativity, originality, and critical thinking. Writing (text and code) is a skill that you must nurture over time in order to develop your own individual voice, style, and view.

Not Allowed

Important

  • Working with or getting help from others on exams and individual quizzes
  • Copying code from another student’s homework and presenting it as your own work.
  • Copy/paste from AI tools or internet sources without customization, citation or explanation
  • Getting your sibling/friend/colleague to write code for you
  • Submitting any assignment that is not 100% your own personal effort.

Allowed

Tip

  • Helping each other solve homework problems (concepts or code)
  • Use AI to help explain a concept
  • Use AI to generate starter code that you modify for your own example.
  • Any AI assisted tool provided by me to aid your understanding
  • Copy/paste code from my course notes or your own work on a prior assignment(Encouraged!)

You must read the Syllabus for my full official policy on using AI in this class.

Additional information

The Syllabus contains additional information on

  • Grading breakdown
  • Attendance
  • Late assignments
  • Academic integrity
  • Adding and dropping the course
  • IT/Computer support
  • Disability support
  • Basic Needs
  • Confidentiality and Mandatory Reporting

Important

There will be a quiz on this next week.