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College of Arts & Sciences
Department of Statistics

STAT 600

600—Statistics for Applied Management (3) Introduction to data collection, descriptive statistics, and statistical inference with examples from hospitality, retail, sport, and entertainment management. Focus on selecting, implementing, and interpreting the appropriate statistical methods using software such as Excel and SPSS.

Note: Not for minor or degree credit in Mathematics or Statistics. Does not serve as a prerequisite for STAT 516, 518, 519, or 525.


Usually Offered: Fall (Live, Live Streaming, and Recorded), Spring (Recorded)

Purpose: STAT 600 is designed to introduce the standard methods of data collection, descriptive statistics, and statistical inference for an applied setting. The focus is on choosing the correct method, verifying that the assumptions of the method are met, and interpreting the resulting output. When helpful, computer simulations are used to demonstrate concepts instead of mathematical or theoretical development. Examples are principally selected from hospitality, retail, sport, and entertainment management, and the course is designed to prepare students for both on the job needs and for subsequent graduate work in those fields.

Current Textbook: Business Statistics (2nd edition), by Norean R. Sharpe, Richard D. DeVeaux, and Paul F. Vellman. Addison Wesley, 2012.


Topics Covered Chapter Time
Data Collection - Limitations and sources of bias in observational studies, surveys, and experiments 1-3, 21 1 week
Descriptive Statistics - Graphical and numerical displays for one and two variables; benefits and limitations of measures of center, spread, and correlation; use of SPSS and Excel 4-5 2 weeks
Introduction to Probability - Basic concepts of probability and independence; assumptions of binomail and hypergeometric experiments, normal distribution, and concept of sampling distributions and central limit theorem; quantile-quantile plots 7-10 2 weeks
Confidence Intervals - Basic concepts and methods for one mean and one proportion 11-12 1 week
Hypothesis Tests - Basic concepts and methods for one mean or one proportion 13 1.5 weeks
Methods for Two Populations - Parametric and nonparametric tests for means 14, 23 1 week
Regression and Correlation - Simple linear regression, correlation coefficient, prediction intervals, introduction to multiple regression and model building 6, 16-19 2 weeks
Experimental Design - Analysis of Variance for one-way and two-way designs, interpretation of interactions, mediation and moderation, multiple comparisons, introduction to repeated measrues 21 2 weeks
Categorical Data - Chi-square tests for goodness of fit, homogeneity, and independence; odds ratios; logistic regression 15, 18.6 1.5 weeks

The above textbook and course outline should correspond to the most recent offering of the course by the Statistics Department. Please check the current course homepage or with the instructor for the course regulations, expectations, and operating procedures.  

Contact Faculty: Brian Habing