STAT/MATH 360-02 Probability

Instructor	Tanya Leise
Email	tleise at amherst dot edu
Phone	542-5411
Office	SMudd 503
Office hours	MTWTh 10-11:15am in Mudd 503 Friday 11am-noon in Mudd 503 Tues/Thurs 1-1:50pm in SCCE E202 (Statistics Consulting Room in Science Center) Feel free to drop in whenever my door is open, or make an appointment
TA hours	Also go to the evening drop-in hours of Patrick Liu and Bodhi Nguyen whenever your schedule permits. It's a great way to find other students to study with and you'll have immediate help available if you get stuck. Sunday: Drop-in help 6-8pm (Bodhi) SMudd 014 Monday: Drop-in help 8-10pm (Patrick) SMudd 207 Wednesday: Drop-in help 6-8pm (Patrick) SMudd 014 Wednesday: Drop-in help 8-10pm (Bodhi) SMudd 207
Text	Probability with R by R. Dobrow (Wiley 2014) (freely available as Ebook through Five Colleges library catalog)

Course goals:

• Study the fundamentals of discrete and continuous probability theory, including probability spaces, independence, conditional probability, expectation, variance, and a variety of discrete and continuous distributions. See the course schedule for a more complete list of topics.
• Develop analytic and empirical problem solving skills and develop your probabilistic intuition.
• Learn how to use R and RStudio to support the study of probability through computation and simulations.

Attendance: Class will be chock full of material and activities -- cooperative learning is more effective and more fun than struggling through material on your own. If you do miss a class, it is your responsibility to obtain the material that you missed and to get your assignments handed in to me.

Questions: If you have a question during lecture, please raise your hand and ask it right away. Chances are that other students are wondering the same thing. If a question arises later, feel free to visit my office and we'll work through sample problems until you are comfortable with the mathematics. Always feel free to ask me to slow down as well.

Study advice: Distributed practice and self-testing have been shown to be the most effective ways to study. Distributed practice means you regularly review the definitions, theorems, and techniques and practice some related problems to reinforce long-term memory (at least several times a week, rather than waiting until just before a test and cramming the material into short-term memory). Self-testing means what it sounds like, and can include testing yourself regularly using flashcards of the definitions and ideas or seeing how far you can get in the homework without looking anything up.

Grading: Your course grade will be based on class participation (5%), two midterms and a final exam (15%, 15%, 20% respectively), weekly problem sets and R problems (30%), and a project (15%).

Intellectual Responsibility

• Exams. Your work must be entirely your own, so follow the guidelines of the Honor Code. You are only allowed whatever aids are explicitly stated on the exam (typically your calculator and a single-sided page of notes). Please turn off your cell phone and all other electronics in kindness to your fellow test-takers during in-class exams. You may not use your cell phone during exams except in emergencies, and it can be grounds for receiving a zero on the exam.
• Homework and other assignments. You may study with other students following these guidelines, again following the Honor Code:

1. If you worked with or received help from any source other than me, you should put a note on the front of your homework saying, "I worked with <names>." Make sure your name stands out as the author of your homework.
2. Working together does not mean that one of you does the first half of the homework set and the other does the second. Everyone should work on every problem and write up their own solution (not copy from another student or source).
3. Each student must hand in his or her own problem set on which you did your own write-up of each problem.
4. Do not copy someone else's solution, and do not seek out and copy answers found on the web or the solutions manual—you will not learn anything and it is plagiarism. I encourage you to discuss problems with others, but then you must be able to work out the solution on your own again and write it down yourself.
5. Sending or receiving a copy of a file that contains student work violates the Honor Code and will be treated as plagiarism. You may talk with others about strategies for solving a problem in R, but please do not share files.
6. If you are unsure what agrees or does not agree with the precepts of intellectual responsibility in this course, feel free to talk to me about it.
7. Your project should be your own individual work, with all sources used clearly cited. You are welcome to come to me for assistance with the project and anything else in the course.

Homework Guidelines

• All problem sets are due at THE START OF CLASS. Late homework will receive half credit for homework handed in after start of class but within 2 class days (e.g., homework due Monday will get half-credit if handed in after the start of class on Monday through Wednesday start of class, and will not accepted after that).
• If you are unable to attend class due to illness or an emergency, let me know as soon as you can and we will work out an appropriate schedule for assignments.
• Your name should be written on all pages, in case any get separated.
• Problem solutions must be written out in the order they were assigned.
• Multiple pages must be stapled or clipped together.
• Homework should be neat and well-organized. No dog ears. No messy edges from notebook paper.
• Where appropriate, please box or highlight final answers. In general, try to make your answers readable and easy to find. Always keep the grader happy!
• As mentioned elsewhere, no copying!

Inclusion and Accessibility
I strive to make all my courses welcoming to all students. I am happy to discuss your learning needs and strategies to best support your academic success. If you have a documented disability that requires accommodations, please register with Accessibility Services at the college, and contact me to let me know what accommodations you will need for this course. Whenever possible, please give me at least two weeks advance notice to implement these accommodations.

Course Expectations and Policy

• You are expected to attend class regularly and actively engage in problem solving and R work during class. Repeated unexcused absences is grounds for loss of all class participation credit.
• Read the book. Going over sections to be covered in class before class will help you learn the material much faster. It really works and is worth the extra time management.
• Please let me know when you may miss class so we can make alternate arrangements as needed for your situation (illnesses, interviews, family emergencies, etc).
• Bring your laptops to class regularly. If you don't have a suitable laptop, let me know and we'll arrange a loaner from the college.
• Ask for help right away whenever you need it. Productive struggle can be good for deep learning, but always seek help when it's not feeling productive and when you need support for background material like counting principles or calculus techniques.
• Practice, practice, practice! Probability, like other mathematics, is best learned through lots of active engagement by working problems.

Course Resources

Don't struggle alone! You have many options for getting help with this course.

• Me. Feel free to come to my office hours, make an appointment by email or phone, or simply try stopping by my office—you are welcome whenever my door is open. If you have some anxiety about taking math exams, please come see me and we can work together on building your math confidence.
• Course TAs. Patrick Liu and Bodhi Nguyen will hold weekly evening office hours.

• Homework. Mathematics is learned ACTIVELY, not passively. You can't absorb math through listening or reading, even if you think you understand it all.
• Textbook. I won't go over everything that is contained in the text, and I will try to avoid doing the same examples. Hence your textbook in an important independent source of information and you should read it!
• Lecture notes. Reviewing the notes you take in lecture will give you a chance to see the material again after you have had some time to assimilate it.
• Your classmates. Discussing math with others can help you think through the concepts. Explaining an idea you already understand will deepen your comprehension, and for the concepts that you don't understand well, the explanation of a peer may be more helpful than mine or the textbook's.
• Library and online resources. There are a variety of books covering probability in the library that you may find it helpful to peruse, which can be very helpful if the textbook doesn't explain a topic in a way that makes sense to you or if you want to see some further examples. There are also many online resources explaining concepts and giving further examples that are easily found by searching for key terms.

To the STAT 360 Homework Schedule