Course Syllabus

MATH 2040 Applied Statistics

Course 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).

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

1. 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.
2. 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.
3. 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.
4. 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.

Course 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 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 various groups of people. In this way, we encourage students from all 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.