Course Syllabus
Course: MATH 3040
Division: Natural Science and Math
Department: Mathematics
Title: Statistics for Scientists and Engineers
Semester Approved: Spring 2023
Five-Year Review Semester: Fall 2027
End Semester: Fall 2028
Catalog Description: This is a first course in statistics for STEM majors. Topics will include graphing techniques, probability theory, discrete and continuous distributions, descriptive statistics, and statistical inference (confidence intervals and hypothesis testing, including linear regression and one-way ANOVA). Proficiency with integral calculus is required.
Semesters Offered: Fall
Credit/Time Requirement: Credit: 3; Lecture: 3; Lab: 0
Prerequisites: MATH 1210
Justification: Many 4-year STEM degrees require a calculus-based statistics course and sister schools in the USHE system have a similar course. This course will fulfill this statistics requirement, especially for the BS in Software Engineering at Snow. This course is designed to transfer as Stat 3000 at Utah State University, Math 3070 at University of Utah, and Math 3410 at Weber State University.
Student Learning Outcomes:
Understand the meaning of statistical measures (including mean, proportion, standard deviation) and be able to calculate each of them for a given data set.
The above mentioned measures are critical building blocks for understanding and summarizing a data set and performing data analysis. Each student's ability to compute these values will be assessed through the following measures: homework, quizzes, exams, and/or projects.
Be able to take a given problem and, as appropriate, complete a hypothesis test or compute a confidence interval.
A key focus of a first statistics course is to be able to analyze data for significance or meaning. Depending on the data, one of the many different procedures must be performed. Each student's ability to compute these values will be assessed through the following measures: homework, quizzes, exams, and/or projects.
Be able to make an appropriate real-world conclusion based on the results of the hypothesis test or confidence interval.
While being able to perform statistical calculations is essential, being able to give real-world conclusions based on the results of the computations provides meaning and purpose to this field of study. Mastery of this skill will be assessed through the following measures: homework, quizzes, exams, and/or projects.
Content:
This course will include:
• probability theory
• discrete and continuous probability distributions
• descriptive statistics & visualizations
• inferential statistics
• confidence intervals and hypothesis tests for one and two means
• confidence intervals and hypothesis tests for one and two proportions
• linear regression
• one-way ANOVA
• introduction to data science
In this class, we are determined to foster an environment of inclusion, diversity, openness, and respect for the many differences that will enrich the Snow College community, including race, ethnicity, religion, gender, age, socioeconomic status, national origin, language, sexual orientation, disability. Specifically, we will present and use data from a diverse group of people. In this way, we encourage students from a variety of backgrounds to find relevance in statistics as it relates to them personally. Using, analyzing, and collecting data from other perspectives will help students connect to those who may have different experiences. The classroom will always be a safe environment where all are welcome to share personal views and opinions without judgement.
Key Performance Indicators:
Student mastery of the learning outcomes will be assessed by:
Homework 5 to 20%
Quizzes 0 to 15%
Projects 0 to 25%
Exams 40 to 70%
Representative Text and/or Supplies:
Anthony Hayter, Probability and Statistics for Engineers and Scientists, current edition, Brooks/Cole/Cengage Learning
Openintro Statistics (OER)
Pedagogy Statement:
Instructors will use a variety of teaching methods including lectures, readings, activities and projects both inside and outside of class, and/or technology activities that may require either the use of a laptop in class or a visit to a computer lab. Students will be encouraged to think critically and creatively. In the classroom, diversity will be valued and we will strive for inclusivity. Data sources used in class will be from and about a diverse group of people. Different opinions and backgrounds will be presented and welcomed. Students from all backgrounds will be encouraged to share their own opinions without judgement.
Instructional Mediums:
Lecture
Maximum Class Size: 28
Optimum Class Size: 20
