QMM 2400 - Statistical Methods for Bus I (3)

Monday,Wednesday,Friday

01:20 PM - 02:10 PM

Main Campus Campus | Varner Hall | Room 205

Descriptive statistics, probability, probability distributions, sampling distributions, estimation, and hypothesis tests. Emphasizes business applications and computer analysis of data. Includes report writing and computer projects, and presentations. Satisfies the university general education requirement in the knowledge applications integration area. Prerequisite for knowledge applications: completion of the general education requirement in the formal reasoning knowledge foundation area.
Prerequisite(s): MTH 1221 or MTH 1222 or MTH 1441 or (MTH 1331 and MTH 1332) or MTH 1554 and MIS 1000 or CSI 1300 with a minimum grade of (C) in each course, and sophomore standing.

By applying the methods taught in the MTH 121 prerequisite course, QMM 240 builds on MTH 121 by using concepts such as linear equations, independent and dependent variables, algebraic functions, and graphs to evaluate and apply knowledge in a field outside of the student’s major area of study. It also builds on prerequisite courses in information technology (MIS 100 or MIS 200 or CSE 125 or CSE 130) for basic concepts and terminology of computing and desktop application software (Excel, Word) to perform calculations and write reports on homework assignments involving business-oriented applications of statistics. By applying the principles taught in prerequisite courses, QMM 240 evaluates and applies knowledge in a field outside of the student’s major area of study to address problems facing business managers and other administrators. QMM 240 applies knowledge in a field outside of the student’s major area of study to calculate descriptive statistics, calculate probabilities from given probability functions, construct confidence intervals using appropriate formulas, calculate test statistics in hypothesis tests, and create graphs of functions. Applications include using the rules of algebra to calculate sums, test statistics, probabilities, combinations, permutations, and sample sizes. Concepts of functions (rules, tables, equations) are used to define random variables and interpret their domains and ranges. The concept of graphs of functions is appplied to probability distributions. The concept of an exponential function is applied to the normal and Poisson probability density functions.

The cross-cutting capacity is critical thinking. Students learn to organize data and use it to improve decision-making in business or in not-forprofit organizations (e.g., government, health care). Because this course applies knowledge from prerequisite courses along with methods taught in this course to problems of managerial decision making, its content enhances students’ critical thinking skills. Students also learn to avoid common pitfalls in reasoning from data (e.g., generalization from non-random samples, misinterpretation of confidence intervals, incorrect interpretation of p-values in hypothesis tests). Writing is not a major component of this course. However, instructors may assign written homework exercises and/or computer projects to individuals or teams. Because of the class size, such written assignments are limited in scope and frequency.

Office: 423 Elliot Hall Office

• Understand the roles and limitations of statistics in addressing decision problems faced by individuals, firms, organizations, and public agencies, and the contexts in which such problems arise. 
• Organize, summarize, compare, and analyze univariate data. 
• Recognize and apply common probability distributions to situations that may arise in business contexts (e.g., binomial, Poisson, normal). 
• Create and interpret confidence intervals for the mean and proportion, and estimate required sample sizes for desired levels of precision. 
• Perform hypothesis tests for the mean and proportion, and recognize situations in which they would be appropriate. 
• Understand Type I error, power, and the role of p-values in hypothesis tests. 
• Use computers confidently and effectively in the previous tasks.