Course Syllabus
Course: MATH 2040
Division: Natural Science and Math
Department: Mathematics
Title: Applied Statistics
Semester Approved: Spring 2022
Five-Year Review Semester: Fall 2026
End Semester: Fall 2027
Catalog Description: Applied Statistics is the study of the nature of statistical reasoning and includes topics such as descriptive statistics, sampling and data collection, probability, hypothesis testing including Chi Square and Analysis of Variance, correlation, and regression. This course is primarily for business and mathematics or statistics majors. Graphing calculator required (TI-83/84 preferred).
Semesters Offered: Fall, Spring
Credit/Time Requirement: Credit: 4; Lecture: 4; Lab: 0
Prerequisites: MATH 1050 or MATH 1080 with a C or better
Justification: This course is part of the pre-business core across Utah institutions. It is a required course for many accounting and business administration majors. It also fills the statistics requirement for some mathematics majors. This course is equivalent to statistics courses at many state institutions although they have different course numbers and are offered by various departments.
Student Learning Outcomes:
Students will be familiar with many common graphs and charts and will be able to create an appropriate graph or chart for a given data set. To become informed citizens, students need to know how to correctly read the graphs they will encounter in daily life (newspapers, magazines, advertisements, etc.). By learning how to make graphs from data, students deepen their knowledge of graphs and the meaning they convey. This ability to make appropriate graphs will be assessed on quizzes and exams.
Students will understand the meaning of statistical measures (mean, median, 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 data and performing data analysis. Each student's ability to compute these values will be assessed through questions on quizzes and exams.
Students will be able to complete a hypothesis test or compute a confidence interval for given data. A fundamental focus of introductory statistics is to analyze data for significance or meaning. Depending on the desired statistic, one of many different procedures must be performed. Each student's ability to perform these calculations will be measured through contextual problems on exams.
Students will be able to make an appropriate real-world conclusion based on the results from the hypothesis test or confidence interval. While being able to perform statistical computations is essential, being able to give real-world conclusions based on the results provides meaning and purpose to this field of study. Mastery of this skill will be measured through exams, and, at the instructor's discretion, student projects.
Content:
This course will include:
• descriptive statistics: graphical methods and numerical methods
• probability and probability distributions: general rules, continuous and discrete probability distributions (normal, binomial, Poisson)
• inferential statistics: confidence intervals for mean, proportion, and standard deviation taken from one and two populations; hypothesis tests for mean, proportion, and standard deviation taken from one and two populations, chi-square tests of independence and goodness of fit; ANOVA
• simple and multiple linear regression
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 learning will be evaluated using:
Homework 5 to 20%
Quizzes 0 to 15%
Midterms or Chapter Exams 20 to 70%
Presentations / Projects 0 to 15%
Comprehensive Final Exam 15 to 35%
Representative Text and/or Supplies:
OpenIntro Statistics, current edition: https://www.openintro.org/book/os/
Graphing calculator required (TI-83/84 preferred).
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
Online
Maximum Class Size: 36
Optimum Class Size: 25
