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Statistics, a branch of applied mathematics, studies the methodology for the collection and analysis of data and the use of data to make inferences under conditions of uncertainty. Statistics plays a fundamental role in the social and natural sciences, as well as in business, industry, and government.
Statistical practice includes: collection, exploration, summarization, and display of data; design of experiments and sampling surveys; drawing inferences and making decisions based on data and assessing the uncertainty of such inferences and decisions; and the construction of mathematical models for analysis of random processes. Probability forms the conceptual foundation and mathematical language for the inferential aspects of statistics.
The statistics program is offered cooperatively by the Departments of Economics, Mathematics, Psychology, and Sociology. The program is administered by an Interdisciplinary Statistics Committee headed by the Statistics Program director, who is appointed by the dean of the Division of Social Sciences. The statistics minor is administered by the Department of Mathematics. Students interested in a statistics minor are encouraged to discuss course selection with a statistics faculty member from any discipline.
Faculty: Selected faculty from the Departments of Economics, Mathematics, Psychology, and Sociology.
Statistics Minor: A minimum of 16 semester hours to include Statistics 341, at least 8 hours from among the other statistics courses (Statistics 231 and Statistics 241 cannot both be counted toward the minor), and Computer Science and Computer Engineering 144 or 220.
The statistics courses chosen for a statistics minor will vary with the interests of the student. Some typical programs leading to a statistics minor are listed below; a computer science course must be added to each list.
For students interested in mathematics, graduate or professional work in statistics, or an actuarial career:
Statistics 341, 342, 348
For students interested in economics or business:
Statistics 231 or 241; 341, Economics 344 or Statistics 341; 342, Economics 344
For students interested in other social sciences:
Statistics 231 or 241; 341; Economics 344 or
Statistics 231 (Psychology students should take designated sections of
Statistics 231.)
For students interested in natural sciences:
Statistics 341, 342, 348 or Statistics 231 or 241, 341, 348
231 Introductory Statistics - MR
Descriptive statistics: measures of central tendency and dispersion.
Inferential statistics: generalizations about populations from samples
by parametric and nonparametric techniques. Methods covered will
include estimation, hypothesis testing, correlation analysis,
regression, chi square, and ANOVA analysis. Includes a required
computer lab. Students should register for the lab corresponding to
their lecture section. (May not be taken for credit after 341 has been
taken.) I II (4)
341 Introduction to Mathematical Statistics - MR
Description of data (univariate and bivariate), introduction to
probability (axioms, discrete and continuous random variables,
expectations), special distributions (binomial, Poisson, normal,
gamma), statements of law of large numbers and central limit theorem,
elements of experimental design (control, randomization, blocking),
sampling distributions, point estimators (bias, efficiency, methods of
moments and maximum likelihood), confidence intervals, hypothesis
tests, regression (if time permits). Prerequisite: MATH 152.
(Crosslisted with MATH 341) I (4)
342 Probability and Statistical Theory - MR
Continuation of Math/Stat 341. Topics may include: joint, marginal and
conditional distributions, correlations, distributions of functions of
random variables, moment generating functions, Chebyschev's inequality,
convergence in probability and limiting distributions, introduction to
inference in regression and one-way analysis of variance, introduction
to Bayesian and non-parametric statistics, power test and likelihood
ratio tests. Prerequisite: MATH. (Crosslisted with MATH 342.) a/y II (4)
343 Operations Research - MR
Quantitative methods for decision problems. Emphasis on linear
programming and other deterministic models. Prerequisite: 231 or
equivalent. (Crosslisted with ECON 343.) II (2)
344 Econometrics - MR
Introduction to the methods and tools of econometrics as the basis for
applied research in economics. Specification, estimation, and testing
in the classical linear regression model. Extensions of the model and
applications to the analysis of economic data. Prerequisite: 231.
(Crosslisted with ECON 344.) (4)
348 Applied Regression and Analysis and ANOVA - MR
Linear, multiple and nonlinear regression, regression diagnostics and
violations of model assumptions, analysis of variance, exper-imental
design including randomization, and blocking, multiple comparisons,
analysis of covariance. Substantial use of a stati-stical computer
package and an emphasis on exploratory analysis of data. Prerequisite:
341 or consent of instructor. a/y II (Crosslisted with MATH 348.) (4)
491 Independent Studies - MR (1-4)
500 Applied Statistical Analysis
(Will not count for statistics minor) An intensive introduction to
statistical methods for graduate students who have not previously taken
Introductory Statistics. Emphasis on the application of inferential
statistics to concrete situations. Topics covered include measures of
location and variation, probability, estimation, hypothesis tests, and
regression. (Crosslisted with ECON 500.) (4)