Applied Statistics

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Program Requirements | Graduate Courses

Graduate Certificate in Applied Statistics

Program requirements for the Graduate Certificate in Applied Statistics Program (15 hours)


Program Requirements

Core Courses (9 hours )

STAT 7340 Advanced Statistical Methods I
STAT 7341 Advanced Statistical Methods II
STAT 7342 Introduction to SAS

Elective Courses (6 hours)

Students must take 6 hours at the 5000-level or above. Courses must be related to statistics or directly support statistics. Elective courses can also be statistic courses from a specific discipline offered by other departments. The director of the program must approve elective courses for credit toward the Graduate Certificate in Applied Statistics.

Students who finish the Graduate Certificate in Applied Statistics and chose to get a Master of Science in Mathematical Sciences with an emphasis in Applied Statistics can transfer the 15 hours toward the Master’s degree program.


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Courses in Statistics

STAT 7340 Advanced Statistical Methods I
Prerequisite: A grade of C or greater in MATH 1451 and STAT 3352 or equivalent. This course is designed to cover the more common advanced statistical concepts and methods. Probability theory, collecting data, sampling, inference, interval estimation, tests of hypotheses for single mean, two means, proportions, and the use of computer packages.

STAT 7341 Advanced Statistical Methods II
Prerequisite: A grade of B or greater in STAT 7340. This course is designed to cover the more common and advanced statistical concepts and methods. Simple linear regression, multiple linear regression, ANOVA of single factor experiments, ANOVA of multi-factor experiments, non-parametric methods, categorical data analysis, Bayesian decision theory and methods, and the use of computer packages.

STAT 7342 Introduction to SAS
This course is designed to introduce students in all disciplines to conducting data analyses and managing data using the SAS system and SAS programming language. The basics of the SAS language and SAS data sets, reading SAS logs, viewing and printing output, inputting data into SAS, manipulating data and creating new variables using SAS procedures, generating descriptive statistics and frequency distributions using SAS Insight. Performing hypothesise tests and constructing confidence intervals, building categorical models, building and interpreting simple and multiple linear regression models, constructing ANOVA models using SAS procedures and Analyst.

STAT 7343 Programming in SAS
Prerequisite: A grade of B or greater in STAT 7342. This course is designed to introduce students in all disciplines to conducting a deep SAS programming on topics in statistical simulation and computation using the SAS system and SAS programming language. Pseudo-random-variate generation, optimization, Monte Carlo simulation, Bootstrap, and Jackknife methods.
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