QBUS 200 Business Statistics I Course Guide

Course Description 

As we enter the 21st century, the issue facing managers is not a shortage of information but how to use the available information to make better decisions. It is from this perspective of informed decision making that we study statistics. 

Statistical thinking can be defined as thought processes that focus on ways to understand, manage, and reduce variation. Statistical thinking includes the recognition that data are inherently variable and that the identification measurement, control, and reduction of variation provide opportunities for quality improvement.

Statistical methods are applied in all functional areas of business: accounting, finance, management, and marketing. Accounting uses statistical methods to select samples for auditing purposes and to understand the cost drivers in cost accounting. Finance uses statistical methods to choose between alternative portfolio investments and to track trends in financial measures over time. Management uses statistical methods to improve the quality of the products manufactured or the services delivered by an organization. Marketing uses statistical methods to estimate the proportion of customers who prefer one product to another and why they do and draw conclusions about what advertising strategy might be more useful in increasing the sales of a product. 

This course will focus on data collection, data presentation, summarizing and describing data, basic probability, and statistical inference. Students will use computer algebra systems and spreadsheets as tools for performing statistical calculations, creating tables, and generating graphical representations of information.

Specific, Assessable Learning Outcomes 

The student will be able to: 

  1. Understand the meaning and use of statistical terms used in business statistics.
  2. Present and/or interpret data in tables and charts.
  3. Understand and apply descriptive statistical measures to business situations.
  4. Understand and apply probability distributions to model different types of business processes.
  5. Understand and apply statistical inference techniques (including statistical estimation and hypothesis testing) in business situations. 
  6. Understand and apply simple linear regression analysis
  7. Use computer spreadsheet software to perform statistical analysis on data.

Course Outline

  • Data collection
  • Presenting data in tables and charts
  • Summarizing and describing numerical data
  • Using probability distributions to model various types of business processes
  • Statistical inference
  • Hypothesis testing
  • Analyzing variances
  • Statistical estimation

Recommended Teaching Methodology 

This course will be structured in such a way as to facilitate the use of different methods of instruction. Readings, lectures, multimedia presentations, group discussions, and spreadsheet assignments will be used throughout the course. Work will be done individually and/or in small groups. 

The primary focus of the teaching methodologies used will be to prepare the student to understand and apply the statistical tools learned to business situations. Thus ample time will be devoted to interactive learning and student “hands-on” problem solving.

The readings will come from the required text as well as additional material to be provided by the instructor. Lectures and group discussions will enable the instructor and students to expand on the material presented in the readings. 

Recommended Assessment Measures 

The following assessment measures will be used.

  1. Assessment devices (quizzes, graded homework, exams, etc.) should be given throughout the semester, building up to a comprehensive final exam.
  2. The comprehensive final exam will be used to assess the student’s level of understanding of business statistical terms, data collection methods, and data presentation techniques (learning outcomes 1, 2, and 3). Furthermore, it will also be designed to assess the student’s ability to apply descriptive statistical measures, probability distributions, and statistical inference techniques in business situations (learning outcomes 4, 5, and 6).
  3. Problems requiring computer spreadsheet solutions (learning outcome 7) will be assigned and assessed throughout the semester by all instructors.

Statement of Expectations 

This course is one of the core courses in the business curriculum. It is normally taken during the student’s second year of full-time studies. 

To attain the desired levels of proficiency, it is required that students attend class prepared to participate in interactive learning using tools such as the graphical calculator and textbook. Students should remain actively engaged in the material covered during class. 

Of course this is not all that is needed, as classroom success is also influenced by student preparation outside the class. It is therefore imperative that students complete out-of-class assignments and textbook reading in a timely fashion. Students will develop and retain the knowledge and skill set described above by continual practice, thereby slowly building and adding onto their knowledge base. “Cramming” in the days before a test not only is not an effective way to learn the skills necessary to employ statistical reasoning in the business environment. 

Lastly, it is expected that if you have a question about any course material you will ask those questions so that they may be answered. There are a variety of sources from which answers will come, including (but by no means limited to) the textbook, the QBA Help Lab, a tutor, classmates and MOST IMPORTANTLY the professor, either in-class or during their office hours. Remember that an unasked question is an answer never given. 

Prerequisite Knowledge

The most important prerequisites are an interest in the subject, the willingness to commit the necessary resources in terms of time and intellectual effort, and the willingness to actively participate in the learning process.
Students should have a fundamental understanding of applied algebra and applied calculus. This will normally be satisfied by successful completion of QBUS-100 and QBUS-110 or the equivalent.
Students should possess proficiency with a computer spreadsheet program. This proficiency will be demonstrated in one of two ways:

  1. Passing the Computer Science Department spreadsheet competency exam
  2. Successful completion of CSIS 010 or CSIS 011 or the equivalent transfer credit.

Institutional Mechanism for Providing Feedback for Continuous Quality Improvement

The Quantitative Business Analysis department will annually review assessment results for this course. Specifically, assessment results in each of the eight learning outcome areas will be analyzed to determine the level of success in achieving these learning outcomes. Any deficiencies in achieving learning outcomes will be addressed and appropriate changes designed to improve the success in achieving these learned outcomes.