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Department of Statistics

Turning data into knowledge to solve real world problems

Courses that Contain Some Statistical Content Offered by Other Departments

Courses within the School of Natural Resources

  • NRES812. Introduction to Geographic Information Systems (NRES 812) (4 cr) Lec 3, lab 2.
    Introduction to the conceptual foundations and applications of computer-based geographic information systems (GIS).GIS database development, spatial data analysis, spatial modeling,GIS implementation and administration. Lab exercises provide practical experience with GIS software.
  • NRES814. Quantitative Methods in Geography (3 cr)
    Prereq: STAT 180 or 380 and 6 hrs geography. Introduction to quantitative techniques utilized in geographic research. Fundamental statistical and mathematical techniques used in analyzing spatial relationships.
  • NRES 808. Microclimate: The Biological Environment (AGRO, GEOG, HORT, METR 808; WATS 408) (3 cr I)
    Prereq: MATH 106 or equivalent; 5 hrs physics; or permission.
    Physical factors that create the biological environment. Radiation and energy balances of earth’s surfaces, terrestrial and marine. Temperature, humidity and wind regimes near the surface. Control of the physical environment through irrigation, windbreaks, frost protection, manipulation of light and radiation. Applications to air pollution research. Instruments for measuring environmental conditions and remote sensing of the environment.
  • NRES 856. Mathematical Models in Biology (NRES 456) (3 cr) Lec 3.
    Prereq: MATH 106 and 107 or permission.
    Biological systems, from molecules to ecosystems, are analyzed using mathematical techniques. Strengths and weakness of mathematical approaches to biological questions. Includes: 1) brief review of college level math, 2) introduction to modeling, 3) oscillating systems in biology, 4) randomness in biology, 5) review of historically important and currently popular models in biology

Other UNL classes with substantial statistical content

  • EDP 859. Statistical Methods (3 cr)
    Computation and interpretation of measures of central position, variability and correlation; introduction to sampling, probability, and tests of significance.
  • EDP *860. Applications of Selected Advanced Statistics (3 cr)
    Prereq: EDPS 859.
    Variety of parametric and nonparametric analyses, including analysis of variance (completely randomized design and various factorial designs), regression analysis, analysis of covariance, full model stepwise multiple regression, chi square Mann-Whitney U, and Wilcoxon test. Understanding and application of these analyses. Appropriate mainframe and microcomputer statistical packages utilized to assist in the numerical analysis of data.
  • EDP 941. Intermediate Statistics: Experimental Methods (SRAM 941) (3 cr)
    Prereq: EDPS 859.
    Computation, interpretation, and application of analysis of variance techniques, including factorial and mixed model designs. Computer and microcomputer software accessed.
  • EDP 942. Intermediate Statistics: Correlational Methods (SRAM 942) (3 cr)
    Prereq: EDPS 859 or equivalent.
    Various correlational-based statistical procedures presented, including linear and nonlinear regression, multiple regression, statistical control, analysis of interactions, the general linear model, factor analysis, and discriminant analysis.
  • EDP 969. Nonparametric Statistical Methods (3 cr)
    Prereq: EDPS 859 or equivalent.
    Presentation of statistical procedures that do not require fundamental assumptions about the distribution property of the variables to be analyzed. Chi Square tests, rank tests of location (Wilcoxen, Mann Whitney, Kruskal-Wallis, Friedman), tests of goodness of fit (Chi Square, Kolmogorov- Smirnoff), tests of randomness (Runs).
  • EDP 971. Structural Equation Modeling (SRAM 971) (3 cr)
    Prereq: EDPS/SRAM 942 and 970; or equivalent.
    Introduction to the techniques of path analysis, confirmatory factor analysis, and structural equation modeling with emphasis on the set-up and interpretation of different models using the LISREL program. Model testing and evaluation, goodness- of-fit indices, violations of assumptions, specification searches, and power analyses.
  • EDP 972. Multivariate Analysis (SRAM 972) (3 cr)
    Prereq: EDPS/SRAM 941 and 942.
    Techniques of multivariate analyses, including multivariate analysis of variance and covariance, multivariate multiple regression, multigroup discriminant analysis, canonical analysis, repeated measures (Multivariate model), and time series. Mathematical models presented and analyzed. Instruction complemented by appropriate statistical software packages
  • CSCE 874. Introduction to Data Mining (3 cr) Lec 3.
    Prereq: CSCE 310; STAT/MATH 380 or STAT 880. CSCE 874 requires a project involving application of data mining techniques to real-world problems.
    Data mining and knowledge discovery methods and their application to real-world problems. Algorithmic and systems issues. Statistical foundations, association delivery, classification, prediction, clustering, spatial data mining and advanced techniques.
  • ECON 817. Introductory Econometrics (3 cr)
    Prereq: ECON 210 or 211 and 212; ECON 215 or equivalent.
    Basic econometric methods including economic model estimation and analyses of economic data. Hypothesis formulation and testing, economic prediction and problems in analyzing economic cross-section and time series data.
  • ECON 957. Econometrics I (3 cr)
    Prereq: ECON 815 or equivalent; STAT 880 or equivalent.
    Matrix-based approach to the construction of statistical economic models, estimation of model parameters, and econometric inference. Multiple hypothesis tests, prediction, and general error structures.
  • ECON 958. Econometrics II(3 cr) Prereq: ECON 957. Continuation of Econometrics I involving a more advanced treatment of statistical economics models. Identification problem and alternative methods of estimating parameters.
  • ECON 959. Econometrics Seminar (3 cr)
    Prereq: ECON 958 with a grade of B or better.
  • IMSE 821. Applied Statistics and Quality Control (3 cr)
    Prereq: IMSE 321.
    Systematic analysis of processes through the use of statistical analysis, methods, and procedures: statistical process control, sampling, regression, ANOVA, quality control, and design of experiments.
  • IMSE 822. Industrial Quality Control (3 cr II) Lec 2, lab 3.
    Prereq: IMSE 321.
    Statistical process control and quality assurance techniques in manufacturing. Control charts, acceptance sampling, and analyses and design of quality control systems.
  • IMSE 922. Quality Engineering: Use of Experimental Design and Other Techniques (3 cr)
    Extension of industrial quality control methods and techniques. Off-line and online quality control methods. Development of quality at the design stage through planned experiments and analyses. Experimental design methods include factorial, 2k, 3k, and factional factorials designs. Includes applied project in design of quality.

Continued

  • IMSE 828. Stochastic Operations Research Models (3 cr)
    Prereq: IMSE 321.
    Techniques for understanding and predicting stochastic system behavior. Probability, Markov chains, queueing analysis, dynamic programming and reliability.
  • IMSE 831. Stochastic Processes (3 cr)
    Prereq: IMSE 828.
    Fundamentals of stochastic processes and their application in modeling production/inventory control, maintenance and manufacturing systems. Markov and semi-Markov chains, Poisson processes, renewal processes, regenerative processes and Markov decision processes.
  • POL *800. Research Methods (SRAM *800) (3 cr)
    Basic techniques used in quantitative political science research. The general linear model. Basic probability theory, ordinary least squares regression, and how to solve problems often encountered when conducting quantitative analyses in political science.
  • PSY 941. Psychometric Methods I (3 cr)
    Prereq: Permission.
    Applications of statistical methods and probability theory to psychological problems. Scaling methods, correlation, chisquare, and graphic methods of studying relationships.
  • PSY 942. Psychometric Methods II (3 cr)
    Prereq: PSYC 941 or permission.
    Psychophysical methods, analysis of variance, design of experiments, advanced correlation analysis.
  • PSY 943. Factor Analysis (3 cr)
    Prereq: PSYC 942 or EDPS 971 or permission.
    Analysis of mental ability and personality into sets of variables.
  • PSY 944. Multilevel Models for Longitudinal Data (3 cr) Lec 3.
    Prereq: PSYC 941 and 942.
    Applications of the multilevel model (hierarchical linear model, general linear mixed model) for examining longitudinal data, random effects (growth curve) models, within person variation models, and prediction of between- and within-person variation using covariates.
  • PSY 945. Advanced Multilevel Models (3 cr) Lec 3.
    Prereq: PSYC 944.
    Advanced applications of the multilevel model (hierarchical linear model, general linear mixed model) for examining multiple sources of variation, models for crossed sources of nesting, three levels of nesting, heterogeneous variances, multivariate outcomes, and non-linear outcomes.
  • PSY 948. Latent Trait Measurement Models (3 cr) Lec 3.
    Prereq: PSYC 941 and 942.
    Contemporary measurement theory and models for scale construction and evaluation, confirmatory factor analysis, and item response modeling.
  • SOC 863. Advanced Methods of Social Research II (SRAM 863) (3 cr)
    Intensive analysis of the logic and techniques of sociological analysis: techniques of scaling and index construction; contingency table analysis; measures of association; parametric and nonparametric statistical inference; and generalizations from systematic findings.
  • SRAM 865. Survey Design and Analysis (SOCI 865) (3 cr)
    Basic issues related to the design and analysis of sample surveys. Basics of questionnaire construction, sampling, data collection, analysis and data presentation.
  • SRAM *896. Practicum in Survey Research and Methodology (3 cr)
    Prereq: Permission.
    Application of theory and research gained during internship.
  • ACT 810. Introduction to Credibility, Smoothing of Data, and Simulation (3 cr) Lec.
    Prereq: STAT 463.
    Full, partial, Buhlmann and Buhlman-Straub credibility models. Introduction to empirical Bayes and statistical distributions used to model loss experience. Application of polynomial splines to actuarial data. Simulation of both discrete and continuous random variables in context of actuarial models. Simulation to estimate “p-value” of hypothesis test. “Bootstrap method” to estimate the mean squared error of an estimator.
  • ACT 825. Survival Models (3 cr) Lec.
    Prereq: STAT 883 with grad of C or better.
    Parametric and tabular survival models. Estimation based on observations that might not be complete. Concomitant variable. Use of population data. Application to groups of people with impaired lives.
  • BIO 951. Quantitative Analysis in Biology (4 cr)
    Prereq: Permission.
    Surveys the kinds of quantitative problems that arise in biological research, particularly in field-oriented disciplines such as ecology, evolution and behavior, and the quantitative methods used to solve them. Practical learning of the strengths and weaknesses of different methods through the analysis of biological data on microcomputers.
  • BIO 989. Research Design (3 cr) Lec 3.
    Prereq: STAT 801 or equivalent.
    Basic logic of research design and methodology in ecology, evolutionary biology and behavior. Logic of scientific investigation, how to evaluate a dependent variable, the manipulation and control of independent, secondary and confounding variables, independence and pseudoreplication, the use of repeated measures designs and quasi-experimental designs.
  • BIO 951. Quantitative Analysis in Biology (4 cr)
    Prereq: Permission.
    Surveys the kinds of quantitative problems that arise in biological research, particularly in field-oriented disciplines such as ecology, evolution and behavior, and the quantitative methods used to solve them. Practical learning of the strengths and weaknesses of different methods through the analysis of biological data on microcomputers.
  • 889. Stochastic Processes and Advanced Mathematical Finance (3 cr) Lec 3.
    Prereq: MATH 221/821 and/or STAT/MATH 380.
    Properties of stochastic processes and solutions of stochastic differential equations as a means for understanding modern financial instruments. Derivation and modeling of financial instruments, advanced financial models, advanced stochastic processes, partial differential equations, and numerical methods from probabilistic point of view.
  • 828. Principles of Operations Research (3 cr)
    Prereq: MATH 814 or permission and STAT 880 or IMSE 321 or equivalent.
    Introduction to techniques and applications of operations research. Includes linear programming, queueing theory, decision analysis, network analysis, and simulation.