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  • STAT 4700: Large-Scale Data
    3.00 Credits
    Middle Tennessee State University

    The analysis and applications of large-scale data sets. Scalable machine learning and data mining applications in a practical clinical environment. Statistical software used in the application of these techniques.
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  • STAT 5140: Probabilistic Statistical Reas
    3.00 Credits
    Middle Tennessee State University

    Prerequisite: Must be enrolled in the Master of Science in Professional Sciences program; graduate level. Focuses on probability and statistics concepts. Topics include binomial and normal probabilistic modeling; important statistical concepts such as confounding, randomization, sampling variability and significance; statistical testing of significant differences and associations; and design experiments to test research hypotheses.
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  • STAT 5190: Mathematical Statistics II
    3.00 Credits
    Middle Tennessee State University

    Prerequisite: STAT 3150 or equivalent. Theory of statistical inference. Topics include sampling distributions, decision theory, estimation, test of hypothesis, regression analysis, analysis of variance, and selected applications.
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  • STAT 5200: Statistical Methods Forecast
    3.00 Credits
    Middle Tennessee State University

    Prerequisite: STAT 4190. Application of the regression model in forecasting regression and exponential smoothing methods to forecast nonseasonal time-series, seasonal series and globally constant seasonal models, stochastic time series models; and forecast evaluation. (Prepares actuarial science students for the Society of Actuaries Exam #120 and Exam Part 3A administered by the Casualty Actuarial Society.)
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  • STAT 5320: Probability Stochastic Process
    3.00 Credits
    Middle Tennessee State University

    Prerequisite: Two semesters of calculus and STAT 3150 (or MATH 2050) or consent of instructor. Theoretical basis for stochastic processes and use as models of real-world phenomena. Topics include Markov chains, Poisson processes, and Brownian motion and stationary processes. Applications include Gambler's Ruin, birth and death models, hitting times, stock option pricing, and the Black-Scholes model.
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  • STAT 5360: Regression Analysis
    3.00 Credits
    Middle Tennessee State University

    Prerequisite: STAT 3150 or equivalent. Theory and application of regression models. Approaches to model building and data analysis treated. Computation and interpretation of results facilitated through use of statistical software packages.
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  • STAT 5370: Nonparametric Statistics
    3.00 Credits
    Middle Tennessee State University

    Prerequisite: STAT 3150 or equivalent. Statistical tests that require no assertions about parameters or about the form of the population from which the samples are drawn. A wide range of practical problems.
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  • STAT 5380: Experimental Design
    3.00 Credits
    Middle Tennessee State University

    Prerequisite: STAT 3150 or equivalent. Topics include one-way analysis of variance, multiple comparison, multifactor analysis of variance, and various practical issues in experimental design. Computation and interpretation of results are facilitated through the use of statistical software packages.
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  • STAT 5600: Problems in Statistics
    1.00 - 6.00 Credits
    Middle Tennessee State University

    Prerequisites: Senior standing and consent of instructor. Students wishing to enroll must submit a written course/topic proposal to the department prior to the semester in which STAT 5600 is taken. Proposal must be approved prior to student taking the course. At the conclusion of the course, each enrollee must submit a written report to the department.
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  • STAT 6020: Applied Statistical Methods
    3.00 Credits
    Middle Tennessee State University

    Prerequisite: Introductory probability/statistics course or permission of instructor. Contemporary and medical research methodology for biostatistics. Descriptive and inferential statistics including parametric and nonparametric hypothesis testing methods, sample size, statistical significance and power, survival curve analysis, relative risk, odds ratios, chi square modeling, and analysis of variance. Data will be analyzed using statistical software.
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