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Course Syllabus

Course: MATH 2040

Division: Natural Science and Math
Department: Mathematics
Title: Applied Statistics

Semester Approved: Spring 2016
Five-Year Review Semester: Spring 2021
End Semester: Spring 2022

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/statistics majors. Graphing calculator required (TI-83/84 preferred).

Semesters Offered: Fall, Spring
Credit/Time Requirement: Credit: 4; Lecture: 4; Lab: 0
Clock/Hour Requirements: 0

Prerequisites: MATH 1050 or MATH 1080 with a C or better

Justification: This course is part of the pre-business core at all institutions in the state. 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:
Upon successful completion of this course, 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 many 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. 

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 / summarizing a data set and performing data analysis. Each student's ability to compute these values will be assessed through questions on quizzes and exams. 

Be able to take a given problem and, as appropriate, complete a hypothesis test or compute a confidence interval. A fundamental focus of introductory statistics is to be able to analyze data for significance or meaning. Depending on the desired statistic, one of many different procedures must be performed. Through contextual problems on exams, each student's ability to perform these calculations will be measured. 

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. 

This course will include:
• descriptive statistics o graphical methods o numerical methods
• probability and probability distributions o general rules o continuous and discrete probability distributions
• normal
• binomial
• poisson
• inferential statistics o confidence intervals for mean, proportion, and standard deviation taken from one and two populations o hypothesis tests for mean, proportion, and standard deviation taken from one and two populations o simple and multiple linear regression o chi-square tests of independence and goodness of fit o ANOVA

Key Performance Indicators:
Student learning will be evaluated using:

Homework (5 - 20%) 

Quizzes (0 - 15%) 

Midterms or Chapter Exams (20 - 70%) 

Presentations / Projects (0 - 15%) 

Comprehensive Final Exam (15 - 35%) 






Representative Text and/or Supplies:
Brase & Brase, Understandable Statistics: Concepts and Methods, current edition, Cengage

Graphing calculator required (TI-83/84 preferred).

Pedagogy Statement:

Maximum Class Size: 36
Optimum Class Size: 25