Course Syllabus

MATH 3040 Statistics for Scientists and Engineers

Course 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.

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

1. 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.
2. 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.
3. 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.

Course 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 scienceIn this class, we foster an environment of 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 variety of people. In this way, we encourage students from various 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.