Southern Utah University

Course Syllabus

Southern Utah University
Southern Utah University
Spring Semester 2026

Introduction to Data Science (Face-to-Face)

MATH 1190-01

Course: MATH 1190-01
Credits: 3
Term: Spring Semester 2026
Department: MATH
CRN: 11285

Course Description

This course introduces the analysis and visualization of data using a high-level computer programming language (e.g., R). It emphasizes conceptual understanding of the data science lifecycle, which includes data collection and organization, sampling and sampling bias, exploratory data analysis and visualization, statistical inference, and prediction. Inference and prediction topics include confidence intervals, hypothesis tests with one and two samples, chi-square tests, ANOVA, and linear regression. (Fall, Spring) [Graded (Standard Letter)] Prerequisite(s): MATH 1010 or MATH 1031 or adequate test score within the last two (2) years - Prerequisite Min Grade: C Is there a standardized test that serves as a prerequisite? If yes, what is the name of the test and minimum score? ACT Math Subscore (21) or ALEKS PPL (40)

Required Texts

 We will be using a variety of open source textbooks and other resources instead of a traditional textbook.  You will also need access to a laptop on which you can load and run R.  We will be heavily utilizing R in this class.  You can download R here: https://cloud.r-project.org/

Learning Outcomes

This course fulfills the general education (GE) requirements in Quantitative Literacy. Upon successful completion of this course, students will be able to:
  1. Use correct terminology and proper notation to explain quantitative or mathematical relationships (equations, graphs, diagrams, tables, data) and to support an argument, assertion, or purpose using quantitative or mathematical evidence; 
  2. Convert quantitative or mathematical information into appropriate mathematical representations and/or models such as equations, graphs, diagrams, or tables, including making and evaluating important assumptions as needed; 
  3. Use algebraic skills and techniques to solve problems, including the ability to identify and correct errors in calculations and understanding the role and proper use of technology in assisting with calculations; 
  4. Draw appropriate conclusions through quantitative or mathematical analysis of data or models, including understanding and evaluating important assumptions in order to recognize the limits of the analysis; and 
  5. Solve concrete and abstract problems across multiple disciplines. 

Course Requirements

Participation (8% of overall grade) Regular attendance and participation is expected at all class meetings.  Class notes will be posted in Canvas for students who miss class.   At the end of each class, a short participation report will be collected.  Your lowest 3 participation scores will be dropped.

Assignments (14% of overall grade) The assigned questions/problems must be worked to an answer and will be graded on completeness, not on correctness.  The work and solutions to the assigned problems should be submitted as a single PDF uploaded into Canvas.  There will be two components to your homework.  

``Short Homework'' assignments are assigned nearly every day after class and will focus on the material covered that day in class.  These assignments will be due at the end of the next academic day.  These assignments will be graded for completeness, not for being correct.  Once the assignment due date has passed, the solutions will become available to you.  Unexcused late homework will not be accepted.  Your three lowest daily ``Short Homework'' scores will be dropped. 

``Long Homework'' assignments will be collected weekly.  These assignments will also not be graded for correctness, but feedback will be provided.  These will typically be due on Thursdays.  You can generally submit these assignments up to one day late, but at a 10\% grade reduction.  

You are strongly encouraged to do your homework as independently as possible.  Try and think about a problem several times before looking for outside help.  Struggling through a problem is the only way to make connections that allow for better understanding, higher test performance and retention.  Everything you turn in should be in your own words and you should thoroughly understand everything you write down.  For all submissions for this class, it is important that you submit your own authentic work that was created with approved resources.  

Unit Quizzes (40% of overall grade) There will be five unit quizzes.  Four will be in the testing center and one will be in the classroom.  Please see Canvas for guidelines regarding notes and calculator/computer use during the quizzes.  The in-class quiz will be an {\bf R} quiz that involves doing some important operations that we have learned in class.  The {\bf R} quiz will be open note.

Smaller Projects (10% of overall grade) There will be two smaller projects assigned during the semester.  The purpose of these projects is to allow you to have some ``hand-on'' experience with data analysis, collection and/or other statistical considerations.

Final Project (12% of overall grade) There will be a project towards the end of the semester where each student must use inferential statistics to answer questions about the data they collect during the semester.  More information on the final project will come later.

Final Exam (16% of overall grade) The final exam will be cumulative and will be given in class at the scheduled final exam time.  For this class, the final is on Wednesday, Apr 22, {\bf 7:00-8:50 a.m.}.  More information on the final exam will be given later.

Course Outline

The outline below is tentative:

Week 1: First principles of statistics and data science
Week 2: Data collection, sampling and sampling bias, introduction to statistics
Week 3: Descriptive statistics continued, Unit Quiz 1
Week 4: Introduction to R
Week 5: Data wrangling in R
Week 6: Data visualization in R
Week 7: Unit Quiz 2 and intro to probability
Week 8: Probability Distributions and Normal Variables
Week 9: The CLT and Unit Quiz 3
Week 10: Spring Break
Week 11: Confidence intervals and hypothesis tests for one parameters 
Week 12: More statistical inference, Unit Quiz 4
Week 13: Confidence intervals and hypothesis tests for multiple parameters
Week 14: Final statistical inference and correlation
Week 15: Regression and Unit Quiz 5
Week 16: Finals: Final Exam and Final Project

Instructor's policies on late assignments and/or makeup work

Short homework assignment are not accepted late.  Your three lowest scores will be dropped.

Participation activities must be completed in class.  Your three lowest scores will be dropped.

Long homework assignments are accepted up to one day late, but with a 10% penalty. 

Exams need to be taken on the scheduled day(s) at the scheduled times.  Early final exams will not be given.

Exams can be rescheduled in case of emergency.  An emergency is an unplanned event over which a student has no control.  Written verification will be required.

Attendance Policy

This class has a face-to-face designation and you are expected to attend and participate in class every day.  If you are feeling ill, please contact me for a make-up option during office hours.  Three in-class activity scores will be dropped.

Course Fees

There is a fee of $3.75 to take this course.

ADA Statement

Students with medical, psychological, learning, or other disabilities desiring academic adjustments, accommodations, or auxiliary aids will need to contact the Disability Resource Center, located in Room 206F of the Sharwan Smith Center or by phone at (435) 865-8042. The Disability Resource Center determines eligibility for and authorizes the provision of services.

If your instructor requires attendance, you may need to seek an ADA accommodation to request an exception to this attendance policy. Please contact the Disability Resource Center to determine what, if any, ADA accommodations are reasonable and appropriate.

Academic Credit

According to the federal definition of a Carnegie credit hour: A credit hour of work is the equivalent of approximately 60 minutes of class time or independent study work. A minimum of 45 hours of work by each student is required for each unit of credit. Credit is earned only when course requirements are met. One (1) credit hour is equivalent to 15 contact hours of lecture, discussion, testing, evaluation, or seminar, as well as 30 hours of student homework. An equivalent amount of work is expected for laboratory work, internships, practica, studio, and other academic work leading to the awarding of credit hours. Credit granted for individual courses, labs, or studio classes ranges from 0.5 to 15 credit hours per semester.

Academic Freedom

SUU is operated for the common good of the greater community it serves. The common good depends upon the free search for truth and its free exposition. Academic Freedom is the right of faculty to study, discuss, investigate, teach, and publish. Academic Freedom is essential to these purposes and applies to both teaching and research.

Academic Freedom in the realm of teaching is fundamental for the protection of the rights of the faculty member and of you, the student, with respect to the free pursuit of learning and discovery. Faculty members possess the right to full freedom in the classroom in discussing their subjects. They may present any controversial material relevant to their courses and their intended learning outcomes, but they shall take care not to introduce into their teaching controversial materials which have no relation to the subject being taught or the intended learning outcomes for the course.

As such, students enrolled in any course at SUU may encounter topics, perspectives, and ideas that are unfamiliar or controversial, with the educational intent of providing a meaningful learning environment that fosters your growth and development. These parameters related to Academic Freedom are included in SUU Policy 6.6.

Academic Misconduct

Scholastic honesty is expected of all students. Dishonesty will not be tolerated and will be prosecuted to the fullest extent (see SUU Policy 6.33). You are expected to have read and understood the current SUU student conduct code (SUU Policy 11.2) regarding student responsibilities and rights, the intellectual property policy (SUU Policy 5.52), information about procedures, and what constitutes acceptable behavior.

Please Note: The use of websites or services that sell essays is a violation of these policies; likewise, the use of websites or services that provide answers to assignments, quizzes, or tests is also a violation of these policies. Regarding the use of Generative Artificial Intelligence (AI), you should check with your individual course instructor.

Emergency Management Statement

In case of an emergency, the University's Emergency Notification System (ENS) will be activated. Students are encouraged to maintain updated contact information using the link on the homepage of the mySUU portal. In addition, students are encouraged to familiarize themselves with the Emergency Response Protocols posted in each classroom. Detailed information about the University's emergency management plan can be found at https://www.suu.edu/emergency.

HEOA Compliance Statement

For a full set of Higher Education Opportunity Act (HEOA) compliance statements, please visit https://www.suu.edu/heoa. The sharing of copyrighted material through peer-to-peer (P2P) file sharing, except as provided under U.S. copyright law, is prohibited by law; additional information can be found at https://my.suu.edu/help/article/1096/heoa-compliance-plan.

You are also expected to comply with policies regarding intellectual property (SUU Policy 5.52) and copyright (SUU Policy 5.54).

Mandatory Reporting

University policy (SUU Policy 5.60) requires instructors to report disclosures received from students that indicate they have been subjected to sexual misconduct/harassment. The University defines sexual harassment consistent with Federal Regulations (34 C.F.R. Part 106, Subpart D) to include quid pro quo, hostile environment harassment, sexual assault, dating violence, domestic violence, and stalking. When students communicate this information to an instructor in-person, by email, or within writing assignments, the instructor will report that to the Title IX Coordinator to ensure students receive support from the Title IX Office. A reporting form is available at https://cm.maxient.com/reportingform.php?SouthernUtahUniv

Non-Discrimination Statement

SUU is committed to fostering an inclusive community of lifelong learners and believes our university's encompassing of different views, beliefs, and identities makes us stronger, more innovative, and better prepared for the global society.

SUU does not discriminate on the basis of race, religion, color, national origin, citizenship, sex (including sex discrimination and sexual harassment), sexual orientation, gender identity, age, ancestry, disability status, pregnancy, pregnancy-related conditions, genetic information, military status, veteran status, or other bases protected by applicable law in employment, treatment, admission, access to educational programs and activities, or other University benefits or services.

SUU strives to cultivate a campus environment that encourages freedom of expression from diverse viewpoints. We encourage all to dialogue within a spirit of respect, civility, and decency.

For additional information on non-discrimination, please see SUU Policy 5.27 and/or visit https://www.suu.edu/nondiscrimination.

Pregnancy

Students who are or become pregnant during this course may receive reasonable modifications to facilitate continued access and participation in the course. Pregnancy and related conditions are broadly defined to include pregnancy, childbirth, termination of pregnancy, lactation, related medical conditions, and recovery. To obtain reasonable modifications, please make a request to title9@suu.edu. To learn more visit: https://www.suu.edu/titleix/pregnancy.html.

Disclaimer Statement

Information contained in this syllabus, other than the grading, late assignments, makeup work, and attendance policies, may be subject to change with advance notice, as deemed appropriate by the instructor.