Disclaimer: This syllabus is subject to change at the discretion of the instructor.

MATH 3070 (Fall '25)

Time & Place: MWF 9:40AM - 10:30AM, AEB 350
Instructor: Firas Rassoul-Agha
E-Mail: firas@math.utah.edu
Office Hour: Mondays 10:40-11:40 AM or by appointment, at LCB 209
Forum: We will be using Piazza for class discussion and answering questions. The system is highly catered to getting you help fast and efficiently from classmates and myself.
Rather than emailing questions, I highly encourage you to post your questions on Piazza. I also highly encourage you to answer your classmate's questions, if you think you know the answer.
One advantage over CANVAS Discussion Board is that you can post anonymously, if you prefer.
You can sign up here but you will need an access code that you can find in the version of the syllabus on CANVAS.


Prerequisites: C or better in MATH 1220 or MATH 1250 or MATH 1270 or MATH 1311 or MATH 1320 or MATH 1321 or an AP Calculus BC score of at least 4.

Corequisite: Students must be enrolled in an accompanying lab section in order to receive credit for this course. The lab will focus on statistical computing using R. Students must pass the lab component in order to pass the course. Please check the syllabus for your lab section for more information.

Course Description: This course will cover descriptive statistics, basic probability theory, discrete and continuous distributions, joint distributions, point estimation, confidence intervals, and hypothesis testing for one or two samples.

Learning Outcomes:
  • Utilize descriptive statistics, and interpret measures of location and variability.
  • Apply the basic properties of probability, and work with conditional probabilities.
  • Work with discrete and continuous random variables.
  • Be fluent in several standard discrete and continuous probability distributions.
  • Work with joint distributions.
  • Understand the foundations of point estimation.
  • Calculate and interpret confidence intervals based on one or two samples.
  • Perform and interpret hypothesis tests based on one or two samples.

    • Textbook: We will follow Probability and Statistics for Engineering and the Sciences, 9th Edition, by Jay L. Devore.

    Lecture Notes: You can find "unfilled" lecture notes here. I highly recommend bringing them (either on your electronic notepad or in printed form) to the lecture and writing your notes on them. This will give you more time to listen to the lecture and yet still write some notes of your own. I will put the "filled" notes here after each lecture.

    Homework is worth 20%. Homework will be posted through Canvas. To submit the homework, you will be asked to upload either pictures or a scan of your work as a file upload through the Canvas assignment page. The homework assignments will usually be due on Mondays by 11:59pm MDT. Please consider uploading your homework well ahead of the deadline, to avoid issues like CANVAS hanging and uploads not working.

    Three in-class 50-minute Midterm Exams are worth 20% each. Make-up midterm exams will ONLY be given if your absence is due to extreme circumstances, for which written documentation of excuse (doctor's note, funeral notice, etc.) is required. They are on September 22, November 3, and December 3, at the same time and place as the lecture.

    Labs are worth 20%. As mentioned above, students must also be enrolled in a lab section of Math 3070. The labs introduce students to the statistical software package R, which you can download for free from the internet. Students must pass the lab component in order to pass the course.

    No final exam.

    Grading Scale: 100≥A>92≥A->89≥B+>86≥B>82≥B->79≥C+>76≥C>72≥C->69≥D+>66≥D>62≥D->59≥E≥0.

    The BEST way to keep up with the pace of this course and to prepare for exams is to solve, at the very least, the assigned homework problems in a timely fashion.
    To learn the subject well you really need to solve as many problems as you can

    Doing the math is the ONLY way to learn math

    Tentatitive Schedule:
    Week Module Textbook Sections (Exam)
    1 Introduction to Statistics and Data Analysis 1.1-1.4
    2 Introduction to Probability
    Conditional Probability, Independence, and Bayes Rule    		 2.1-2.3
    2.4-2.5
    3 Discrete Random Variables
    Excpectation and Variance    		 3.1-3.2
    3.3
    4 Binomial and Poisson Distributions 3.4-3.6
    5 Continuous Random Variables 4.1-4.3
    6 Exam 1. Monday September 22
    The Normal and Exponential Distributions    		 Exam 1 Material: Weeks 1-4, Tentatively: Chapters 1-3
    4.3-4.4
    7 Joint Random Variables 5.1-5.2
    8 Linear Combinations and Sampling Distributions 5.3-5.5
    9 Point Estimation 6.1-6.2
    10 One Sample Confidence Interfals 7.1-7.3
    11 Exam 2. Monday November 3
    One Sample Hypothesis Testing - Part 1    		 Exam 2 Material: Weeks 5-9, Tentatively: Chaptes 4-6
    8.2-8.3
    12 One Sample Hypothesis Testing - Part 2 8.4-8.5, 8.1
    13 Two Sample Inference - Part 1 9.1-9.2
    14 Two Sample Inference - Part 2 9.3-9.5
    15 Exam 3. Wednesday December 3 Exam 3 Material: Weeks 10-14, Tentatively: Chapters 7-9



    Further important information:

  • Updated mandatory syllabus policies regarding the ADA Act, Safety at the U, Addressing Sexual Misconduct, and Academic Misconduct can be viewed here
  • It is the student's responsibility to regularly check their Umail or have it forwarded to an address they check regularly. The Umail is the only way for me to communicate privately with the student. There will be occasions during the semester that we may need to reach out to individual students (e.g. regarding a grade or assignment) and it is in their best interest to respond promptly.
  • I would like to encourage the students to email me only if it is something personal that requires individual attention. For questions about logistics of the class, course material and assignments, and anything else the classmates may wonder about as well, please post a question on Piazza. This way the information is shared quickly to the entire class, and everyone can benefit from seeing other classmates’ questions.
  • The T. Benny Rushing Mathematics Tutoring Center offers free tutoring. The Learning Center has additional tutoring available for our class. The math department also maintains a list of private tutors.
  • Please stay updated by regularly checking: the announcements on Canvas, your Umail, the posts on Piazza, and pay attention to the announcements given in class.
  • Students are expected to log in and check canvas regularly for posted announcements and assignments. Students are also strongly advised to set up notifications for canvas so they do not miss any important notifications.
  • Respectful participation in all aspects of the course will make our time together productive and engaging. Zoom lectures, discussion threads, emails and canvas are all considered equivalent to classrooms and student behavior within those environments shall conform to the student code.
  • COVID-19 Campus Guidlines
  • Drop/Withdrawal Policies: Students may drop a course within the first two weeks of a given semester without any penalties. Students may officially withdraw (W) from a class or all classes after the drop deadline through the midpoint of a course. A “W” grade is recorded on the transcript and appropriate tuition/fees are assessed. The grade “W” is not used in calculating the student’s GPA. For deadlines to withdraw from full-term, first, and second session classes, see the U's Academic Calendar.
  • Wellness at the U: Your personal health and wellness are essential to your success as a student. Personal concerns like stress, anxiety, relationship difficulties, depression, or cross-cultural differences can interfere with a student’s ability to succeed and thrive in this course and at the University of Utah. Please feel welcome to reach out to your instructor or TA to handle issues regarding your coursework. For helpful resources to manage your personal wellness and counseling options, contact the Center for Campus Wellness at 801-581-7776.
  • Office of the Dean of Students The Office of the Dean of Students is dedicated to being a resource to students through support, advocacy, involvement, and accountability. It serves as a support for students facing challenges to their success as students, and assists with the interpretation of University policy and regulations. Please consider reaching out to the Office of Dean of Students for any questions, issues and concerns. 200 South Central Campus Dr., Suite 270. Monday-Friday 8 am-5 pm.