Math 201

Elementary Statistics

Slides

www.inqs.info/m2012_f25/c/1a

Introductions

Introductions
Embedded Peer Educator
Early Success Module
Class Setup
Statistics Activity
Use of Generative AI
Surveys
Extra Credits
Field Trip

Introductions

San Bernardino, CA
CSU Monterey Bay
- BS Biology
San Diego State University
- Master’s in Public Health
UC Riverside
- PhD in Applied Statistics

Introductions

Name
Year
Major
Fun Fact
Career Goal

Embedded Peer Educator

Introductions
Embedded Peer Educator
Early Success Module
Class Setup
Statistics Activity
Use of Generative AI
Surveys
Extra Credits
Field Trip

EPE - Jasmine Torres

This is my 7th year at CSUCI
Triple major in Math (triple emphasis pure, applied, and statistics), Computer Science, and Physics.
Minoring in philosophy and cybersecurity.

Early Success Module

Introductions
Embedded Peer Educator
Early Success Module
Class Setup
Statistics Activity
Use of Generative AI
Surveys
Extra Credits
Field Trip

Assignments

Learner Info Survey
Using the Study Cycle Efficiently

Bloom’s Taxonomy
The Feynman Technique

Class Setup

Introductions
Embedded Peer Educator
Early Success Module
Class Setup
Statistics Activity
Use of Generative AI
Surveys
Extra Credits
Field Trip

Class Setup

Participation
Notebook Assignments
Video Assignments
Classwork Assignments
Exams
Extra Credit

Study Expectations

For every 1 unit of class you take, you are expected to spend ~3 hours outside of class for the course.

Syllabus

www.inqs.info/m201_s26/syllabus

R Programming

This utilized the R programming to conduct data analysis.

R is a powerful tool that allows you to program complex tasks.

Learning R is difficult, but it is the best teacher to teach you how to overcome challenges. Don’t give up when it gets hard and seek out help when needed.

Statistics Activity

Introductions
Embedded Peer Educator
Early Success Module
Class Setup
Statistics Activity
Use of Generative AI
Surveys
Extra Credits
Field Trip

When do you use statistics?

What is the difference between math and stats?

Use of Generative AI

Introductions
Embedded Peer Educator
Early Success Module
Class Setup
Statistics Activity
Use of Generative AI
Surveys
Extra Credits
Field Trip

Use of Generative AI

The use of generative artificial intelligence (AI) to complete any part or all of an assignment/exam is strictly prohibited in this class. This includes, but not limited to, ChatGPT, Claude, Meta AI, and Google Gemini.

You may use AI to enhance you understanding of the material.

You may not upload any course material to any AI platforms such as ChatGPT, Claude, Meta AI, and Google Gemini. Exceptions are allowed for DASS-approved services.

Use of AI

There are consequences when you use of AI:

Educational Mislearning
Trusting AI
Stolen Work
Privacy Concerns
Environmental Impacts
Working Exploitation

Educational Mislearning

The purpose of this class, and college, is for you to learn about critical thinking skills and perseverance. Using AI will only teach you how to get an answer, which may or may not be correct.

You will not develop the skills needed to problem solve a challenge. Additionally, developing grit is essential to become successful in college and life. There is no easy way out and AI is an illusion to your success in life.

To learn something, it requires hours of work! If not years!

Trusting AI

When using AI, you must acknowledge its limitations:

Responses provided may be incorrect
Responses may not be fair
Companies may manipulate responses and/or terms of service for their benefit
Companies may not have your best interst in mind

You should always proceed with caution utilizing these tools!

Stolen Work

Additionally, all these individuals are not receiving any royalties for the work to be used in creating generative AI models.

Inside Higher Ed and The New Yorker highlight individual’s concern of their work being used to train AI models.

Privacy Concerns

The use of generative AI raises concerns of what data is being harvested from us, possibly without informed consent.

When you used any large language models, you do not know what information is being harvested from you.

Do you want to upload your thoughts and ideas to a company that can monetize, and possibly exploit.

Does your Professors consent with you uploading their assignments to large language models?

Stanford provided a report highlighting the risks of our personal data use in large language models.

Environmental Impact

In order to run these large language models, companies need to use a large amounts of energy. This is because large servers are needed to both train and execute a model.

The LA Times reports the potential impact that running AI models in California.

Additionally, Time reports that a ChatGPT query uses ten times more energy than a Google search query, and global AI demands can consume of 1 trillion gallons of water by 2027.

There are also environmental justice questions about where these data centers are constructed.

Worker Exploitation

The Washington Post and Time (Article 1 and Article 2) reported that AI companies utilize “digital sweatshops” to classify data points for model training.

There is a human cost from the Global South, both financially and mentally, to develop the AI models for users in the United States and Europe.

We must be conscious consumers and demand more from these companies to provide safe working conditions and livable wages.