Courses

, LST. 3. Pr. THEA 2650 or Departmental approval. Comprehensive study of specialized makeup, including film and television makeup, mask making, prosthesis, facial hair design, and wig making. Theatre majors who do not earn a grade of "C" or higher must repeat this course.

This course focuses on a comprehensive understanding of statistical and econometric analysis techniques, emphasizing their application in civil engineering and scientific data analysis. It covers model- estimation methods that extend beyond traditional statistics courses, providing students with a broad range of data-analysis applications while discussing underlying theories and limitations for proper comprehension and application.

Continuation of ISE 690 with extension to regression models and nonparametric methods.

An examination of the use of inferential statistics in the analysis of criminal justice data. Major course topics will include the analyses and applications of probabilities, chisquare, t-test, ANOVA, correlations, and bivariate and multiple regression.

This course examines the design and analysis of controlled experiments, demonstrating engineering applications of design of experiments (DOE) in the manufacturing and service industries. Topics include full and fractional factorial designs, response surface methodology, and Taguchi methods. In a semester-long project, students apply DOE to improve a real manufacturing process.

Applications of statistical laws to modern topics such as quantum fluids, critical phenomena, and nonequilibrium systems.

Applications of statistical laws to modern topics such as quantum fluids, critical phenomena, and nonequilibrium systems.

Applications of statistical laws to modern topics such as quantum fluids, critical phenomena, and nonequilibrium systems.

This course provides an overview of commonly used statistical methods in scientific research, with a core focus on generalized linear mixed models for individual studies and meta-analysis for study aggregation. Analyses will be implemented primarily in the R statistical programming environment.

This course is a continuation of Statistical Methods and Computations. Topics include inference for categorical variables, multiple regression, logistic regression, one-way ANOVA, two-way ANOVA. ANCOVA, and nonparametric methods. Data analysis is carried out using the SAS program. Statistical Prereqpackages such as SAS and R will be used. uisite(s): STAT 3350, STAT 4451 or STAT 5551.