Syllabus MATH 314-03 Probability and Statistics for Science and Technology

Section 03: MTWTh 3 - 3.50pm

Holt 291

Contact Information

Edward A. Roualdes (call me Edward)

Email: eroualdes@csuchico.edu

Office hours:

• For the first five weeks of the semester (1/21/2025 - 2/21/2025), my office hours will be in the Meriam Library Innovation Lab:
  • Mondays 1pm - 2.30pm
  • Tuesdays 1pm - 2.30pm
  • Thursdays 11am - 11.50am
  • Fridays 2pm - 3.45pm
  • If none of those times work for you, please email me so that we can find a time that works for us both: eroualdes@csuchico.edu
• After the first five week of the semester, when my two online and asynchronous classes end, I'll reduce my office hours. I don't know how yet: maybe I'll take a poll; maybe I'll just keep the times for which most students showed within the first five weeks.

Course Description

Basic concepts of probability and statistics with emphasis on models used in science and technology. Probability models for statistical estimation and hypothesis testing. Confidence limits. One- and two-sample inference, simple regression, one- and two-way analysis of variance.

Student Learning Objectives / Goals

• Introduce the language of statistics
• Build understanding of random variables and their distributions
• Learn how probability connects to statistics, and statistics connects to data
• Introduce properties of statistics and sampling distributions
• Introduce simple linear and multiple linear regression

Resources

We will primarily use various chapters from the freely available (as PDFs) books

• Probability and Statistics - The Science of Uncertainty, Second Edition. This book is freely available as a PDF online, at the link above, hosted by the second author, Jeffrey S. Rosenthal.
• OpenIntro Statistics v4

We will also draw material from Wikipedia.

If you would like to buy a book, please consider any one of the following:

• A First Course in Probability
• An Introduction to Probability Theory and its Applications
• Weighing the Odds

Additional Requirements

• Access to a laptop will be essential to master the material of this course. If you don’t have immediate and consistent access to a laptop, please speak to me as soon as possible.
• We will learn to code in Python using Jupyter notebooks, both Python and Jupyter notebooks are free, open-source software.

Content Delivery

Lectures are in person at the times listed above. No recordings will be available. As Gil Scott-Heron says, the revolution will not be televised; this class will be live. Or maybe you prefer it's all the way live.

All course materials will be posted to my website: roualdes.us/math314.

Course Communication

The absolute best place to ask a question is during lecture. I understand, though, that not all students feel comfortable asking questions publicly.

If you prefer more private and in person communication, come to office hours.

If you prefer written and identifiable communication, email me at eroualdes@csuchico.edu. If your questions become too complex for email, as judged by me, I reserve the right to ask you to come visit my office to receive your answers in person.

If for any reason I need to address everyone in the course, I will send you an email to your student email account, eg you@csuchico.edu.

Course Grading

Your final grade for this course will be given according to the +/- grading systems, based on the following percentages and scale: 90 to 100, A; 80 to <90, B; 70 to <80, C; 60 to <70, D; <60, F.

Component	Percentage
Homework	10%
Quizzes	40%
2x Live Coding Exams	25% each

Grades will be posted to a shared (between me and each of you, individually and exclusively) Google Sheets file. Access is only granted to your@mail.csuchico.edu account.

So long as you understand the Academic Integrity Policy below, I encourage you to use large language models, like ChatGPT, to help you learn. However, I refuse to grade AI slop. If I judge the content of your work to be AI slop, I reserve the right to give you a failing grade on that assignment. You can meet me in office hours to try to defend your case.

Homework

All homework must be created using Jupyter notebooks, which are then to be shared with me in a manner we mutually agree upon in class via git and private shared GitHub repositories that I will create (we decided in class on 2025-01-21).

You can re-submit a homework that was previously submit on time after it was graded for up to 50% of your missed points back. Think of this as an attempt to correct some of your less-than-correct solutions. As an example, if you earned 80% on a Homework, you can re-submit this Homework with updated answers for a maximum of 10% added to your original score. Thus, you could obtain 90% on a homework for which you originally earned 80%.

Quizzes

Quizzes serve two purposes. First, quizzes ensure you are learning things, separate from what you have convinced a large language model to produce for a homework assignment. Second, quizzes ensure you are regularly attending class.

Quizzes will be on pen and paper, so please bring a pen and paper to every class. In general, quizzes will not necessarily be announced nor scheduled. I reserve the right to hold a quiz for any of the following reasons:

• I'm mean,
• no one has answered a question asked to the class for more than two minutes,
• students have stopped particpating in class,
• students have stopped attending class,
• we haven't had a quiz in a while,
• I'm in the mood for a quiz, or
• other.

I'll drop the lowest $X = 5$ (we decided in class on 2025-01-21) quiz grades when calculating your final grade.

Live Coding Exams

There will be two live coding exams, in which I will give you a prompt and you will program to that prompt while I watch. The prompts will be released ahead of time, so that you have time to practice. You will sign up for a scheduled exam time, sometime near half-way through the semester. Scheduled exam times will take place during our regular class hours and in our regular class room.

If you are unhappy with your results, you can request a maximum of one re-assessment, where we will repeat the setup, but during my office hours. If you choose this option, you will not receive the same prompt as before; you will instead receive a new prompt.

Make-up Policy

Homework can be submit late for a maximum of 50% credit. You can submit a homework as late up until the last day of the regular semester, May 10 at 11:59pm.

You can not re-submit a submit-late Homework, since late Homework will not be accepted.

Quizzes can not be taken after they were assigned.

If you miss your scheduled exam time, you will receive a zero. If you are unhappy with this result, you can request a maximum of one re-assessment as detailed above.

Diversity Policy

Respect: Students in this class are encouraged to speak up and participate during class meetings. Because the class will represent a diversity of individual beliefs, backgrounds, and experiences, every member of this class must show respect for every other member of this class (this includes me).

Academic Integrity Policy

Students are permitted and encouraged to collaborate on all assignments other than quizzes and tests. However, each student must turn in their own work. Further, it is the expressed expectation of this instructor that all students demonstrate integrity and individual responsibility in all actions related to this course. Unethical behavior of any kind is unacceptable and will be prosecuted vigorously. Any sign of cheating in any way on any course assignment will be addressed directly, according to University standards. If you do not understand what plagiarism is, or what cheating entails, you must seek information regarding this matter from the current University Catalog and from me. The consequences of plagiarism begin with a failing grade on the work, and possibly a failing grade in the course, depending upon University action. More information is found on the Student Rights And Responsibilities campus webpage.

The use of artificial intelligence tools are in general not discouraged. At times, ChatGPT or some other large language model may help you through some otherwise challenging coding or writing problems. But submitting Homework exclusively based on such software is considered unacceptable and dishonest. In the end, there's nothing I can do to stop this behavior, other than warn you that future employers can quickly tell the difference between people who know the tools and ideas we'll develop in this course and those who don't. Please do use AI as a tool to help you be more efficient. Please don't become a statistician/data scientist/programmer who can't work without AI.

Disability Support

If you have any disability related needs, please contact Disability Support Service (Colusa Hall 898-5959 or campus information 898-INFO for directions) on campus to obtain the appropriate documentation. Afterwards, email me to identify your needs within the first two weeks of class so that any necessary arrangements can be made.

Confidentiality and Mandatory Reporting

As an instructor, one of my responsibilities is to help create a safe learning environment on our campus. I am required to share information regarding sexual misconduct with the University. Students may speak to someone confidentially by contacting the Counseling and Wellness Center (898-6345) or Safe Place (898-3030). Information on campus reporting obligations and other Title IX related resources are available at www.csuchico.edu/title-ix.

Course Outline

1. Introduction to Python
• Python Numpy Tutorial (with Jupyter and Colab)
2. Distributions and their properties
• random variables
• density functions
• expectations: means and standard deviations
• probability
• percentiles
• distribution functions
3. Estimation
4. Sampling distributions (for the sample mean)
5. Central Limit Theorem (for the sample mean)
6. Confidence Intervals
7. Linear Models
• single mean model
• multiple mean model
• simple linear regression
• multiple linear regression