Southern Utah University

Course Syllabus

Southern Utah University
Southern Utah University
Fall Semester 2025

Applied Statistics (Face-to-Face)

MATH 3150-01

Course: MATH 3150-01
Credits: 3
Term: Fall Semester 2025
Department: MATH
CRN: 31673

Course Description

Introduction to data analytic and applied statistical methods commonly used in industrial and scientific applications as well as in data science. Emphasis will be on the practical aspects of statistics with students analyzing real data sets. Topics covered include analytic and graphical representation of data, exploratory data analysis, regression analysis, principal component analysis, and classification methods. Students will use R throughout the course. (Fall) [Graded (Standard Letter)] Prerequisite(s): (MATH 1040 or MATH 1190 or MATH 3700) and MATH 1050 or instructor permission - Prerequisite Min. Grade: C Registration Restriction(s): None

Required Texts

None. Optional texts include:
The Statistical Sleuth by Ramsey and Schafer;
Statistical Methods for Data Analysis by Ott and Longnecker;
Applied Linear Statistical Models by Kutner et al.

Learning Outcomes

This class serves as an introduction to the statistical software package R for use in statistical analysis and data visualization. This course also aims to provide a solid statistical foundation for applied data analysis. Students will demonstrate proficiency in common data visualization techniques, exploratory data analysis methods, linear regression analysis, logistic regression analysis, principal component analysis topics, and various nonparametric techniques. Additionally, students will demonstrate proficiency in reading and writing code in R to perform data analysis. Students will also be able to apply these statistical methods on real-world data sets.

Course Requirements

Homework/Comment Questions (12% of final grade): Please take the homework seriously and think of each one as writing a report. There will be approximately one homework assignment per set of notes and they will typically be due on Thursdays. You may work with classmates on homework assignments, but you must write (or type) up your own solutions in your own words. These homework assignments will not be thoroughly graded, but I will look over it to check that you gave it a good effort. Once you submit the assignment, the solutions will become available for you to examine. 
In addition to the written homework submission, you will also be required to submit a comment. The idea is that you should submit the assignment, throughout look over the solutions, and then submit any and all questions you have about the assignment. If you have no questions, then you need to indicate that in your comment. The homework is not considered submitted until you leave your comment.

Quizzes (18% of final grade): After nearly all homework assignments, there will be a quiz for you to take in the testing center. The quiz will feature a few questions similar to those you had to answer on the homework for that week. If you understand the homework, these quizzes should go smoothly.

R Quiz (5% of final grade): About half way through the semester, there will be an R Quiz in class that covers important operations you will have learned how to do when doing the homework for this class.

Midterms (40% of final grade): There will be two “semi-cumulative” midterm exams. You may bring a sheet of notes to these exams. These exams will be held in the testing center.

Final Project (25% of final grade): There will be a project toward the end of the semester where each student must use statistical techniques learned in class to analyze a data set to answer a research question of their choice and then present it to the class during a poster sessions. More information on the project will come later in the semester.

Course Outline

This outline is tentative.

Week 1: Introduction and intro to using R
Week 2: More R, exploratory data analysis (EDA) and data visualization
Week 3: More R, hypothesis testing, confidence intervals, ANOVA
Week 4: Two-way ANOVA; multiple comparisons
Week 5: Correlation and regression: simple linear
Week 6: Regression: lack of fit and transformations
Week 7: Regression: simple linear inference and R Quiz
Week 8: Fall Break and regression: multiple linear
Week 9: Regression: multiple linear with inference and Exam 1
Week 10: Regression: diagnostic techniques, model selection
Week 11: Regression: logistic and multinomial logistic
Week 12: Multicollinearity and principal component analysis
Week 13: Nonparametric tests and bootstrapping and Exam 2
Week 14: Thanksgiving break
Week 15: Finish content and final poster presentations
Week 16: Finals: poster presentations

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

Homework can generally be submitted up to one day late with a 10% grade penalty. 

Make-up exams can be arranged with the instructor before the time of the exam. 

Attendance Policy

This class has a face-to-face designation and you are expected to attend class every day unless you are feeling ill. I will be recording class sessions and will post the videos on Canvas.

Course Fees

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

AI Statement

The goal of this class is for your to learn this material. If using artificial intelligence can help you learn, then you may use it. Do not use it as a crutch or use it to completely do your assignments. Always attempt each problem yourself first. Students who over-rely on AI tend to do significantly worse on quizzes, exams, and projects.

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.