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.
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.
