Statistics in Business - IIEI-160

Course Description: This six-week course demonstrates the use and application of modern statistical principles to achieve business improvement, examine the issues of variation of populations, probability, hypothesis testing, and statistical modeling to solve practical questions. The application of decision theory and time-series analysis to assist business are explored.  Case studies are used by students to apply their understanding of course concepts to real-life situations.

Students must have access to MS Excel 2000 or later, and the included statistical support module, or similar program such as MINITAB, to complete some assignments.

Prerequisite: None. Prior basic knowledge of MS Excel suggested.

Course Credit: 3 Credit Hours

Major Course Topics & Course Outcomes

As a result of the group and individual activities included in this course, the student will acquire the following knowledge and skills that can be applied to the workplace:

Business Statistics

• To comprehend why statistical methods are useful in learning about populations
• To know that a variable is quantitative

Descriptive Statistics

• To know what is meant by descriptive statistics
• To describe central tendency and the shape of distribution
• To assess qualitative data in statistical terms

Probability

• To demonstrate an understanding of the concept of probability

Variables

• To differentiate the two types of statistical variables
• To recognize what a binomial distribution represents

Sampling Distribution

• To understand the concept of sampling distribution of a same mean.

Confidence Intervals

• To know about z-based and t-based confidence intervals for a population Mean
• To describe the sample size determination concerns

Hypothesis Testing

• To demonstrate knowledge of null and alternative hypotheses determination
• To know how to test a hypothesis
• To recognize errors in hypothesis testing

Analysis of Variance

• To explain the basic concepts of experimental design

Linear Regression Analysis

• To understand the importance of simple linear regression
• To interpret model assumptions in linear regression

Time Series Forecasting

• To identify the elements required for time series analysis
• To understand advanced models of forecasting such as exponential smoothing

Using Control Charts

• To apply statistics to process control
• To examine the concepts of pattern analysis

Decision Theory

• To discuss the basics of decision theory

Course Texts:

There is one textbook for this course.

Business Statistics in Practice. 4th Edition. Bowerman, B.L. and O’Connell, R.t. Irwin/ McGraw-Hill, Boston, MA  (2007) 0-07-325291-3

Selected Readings Online.

Please note that textbooks are subject to change. Please contact your advisor before purchasing the textbook for your class to confirm.